diff --git a/README.md b/README.md new file mode 100644 index 0000000000000000000000000000000000000000..b4f8f3118909a8fdb47890edb5c892636ed27e3e --- /dev/null +++ b/README.md @@ -0,0 +1,24 @@ +--- +license: mit +tags: +- codex-skills +- ai +- machine-learning +- llm +- web +- dataset +pretty_name: AI Skill MD Dataset +--- + +# AI Skill MD Dataset + +This Hugging Face Dataset repository contains 500 Codex-style skill folders. +Each skill has a required `SKILL.md` file and lightweight `agents/openai.yaml` metadata. + +The repository is intended as a file database of skill definitions only. It is not a Hugging Face Space and contains no app runtime. + +## Layout + +- `skills//SKILL.md`: skill instructions and trigger metadata +- `skills//agents/openai.yaml`: UI-facing metadata +- `skills_index.jsonl`: searchable index of all generated skills diff --git a/skills/a-b-testing-models/SKILL.md b/skills/a-b-testing-models/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..869369a53be60dbe1e5e612724c71ceec926e195 --- /dev/null +++ b/skills/a-b-testing-models/SKILL.md @@ -0,0 +1,29 @@ +--- +name: a-b-testing-models +description: "Guidance for A B testing models in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving A B testing models, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# A B Testing Models + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for A B testing models. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on A B testing models. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/a-b-testing-models/agents/openai.yaml b/skills/a-b-testing-models/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..19a41369097ebd217a2a41fbe49cf1d0a75d4751 --- /dev/null +++ b/skills/a-b-testing-models/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "A B Testing Models" +short_description: "Work on A B testing models for MLOps." +default_prompt: "Use this skill to help with A B testing models in MLOps." diff --git a/skills/ablation-studies/SKILL.md b/skills/ablation-studies/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..525a15d16e186ecba18d4fd136222fd6f2adf71b --- /dev/null +++ b/skills/ablation-studies/SKILL.md @@ -0,0 +1,29 @@ +--- +name: ablation-studies +description: "Guidance for ablation studies in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving ablation studies, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Ablation Studies + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for ablation studies. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on ablation studies. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/ablation-studies/agents/openai.yaml b/skills/ablation-studies/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..28ab5f7bb737fdeea2d04a2f99fb428011d9fd23 --- /dev/null +++ b/skills/ablation-studies/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Ablation Studies" +short_description: "Work on ablation studies for Research And Scientific AI." +default_prompt: "Use this skill to help with ablation studies in Research And Scientific AI." diff --git a/skills/accent-robustness/SKILL.md b/skills/accent-robustness/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..ff45b9a16bc98928140ecb1aca7810fb1b007035 --- /dev/null +++ b/skills/accent-robustness/SKILL.md @@ -0,0 +1,29 @@ +--- +name: accent-robustness +description: "Guidance for accent robustness in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving accent robustness, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Accent Robustness + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for accent robustness. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on accent robustness. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/accent-robustness/agents/openai.yaml b/skills/accent-robustness/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..c4b014c1ccd30f556135bd1de7dd8db02e896828 --- /dev/null +++ b/skills/accent-robustness/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Accent Robustness" +short_description: "Work on accent robustness for Speech And Audio." +default_prompt: "Use this skill to help with accent robustness in Speech And Audio." diff --git a/skills/accessibility-for-ai-products/SKILL.md b/skills/accessibility-for-ai-products/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..e6dd7fa07b08e87c224764984e62615cb6ff1a2e --- /dev/null +++ b/skills/accessibility-for-ai-products/SKILL.md @@ -0,0 +1,29 @@ +--- +name: accessibility-for-ai-products +description: "Guidance for accessibility for AI products in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving accessibility for AI products, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# Accessibility For AI Products + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for accessibility for AI products. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on accessibility for AI products. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/accessibility-for-ai-products/agents/openai.yaml b/skills/accessibility-for-ai-products/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..08b555dcc16f935b4fc91b0c7de152ecc883c0f7 --- /dev/null +++ b/skills/accessibility-for-ai-products/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Accessibility For AI Products" +short_description: "Work on accessibility for AI products for AI Product And UX." +default_prompt: "Use this skill to help with accessibility for AI products in AI Product And UX." diff --git a/skills/action-recognition/SKILL.md b/skills/action-recognition/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..27bdaec0ca0c27f705445799b8cdbdbe66afaa57 --- /dev/null +++ b/skills/action-recognition/SKILL.md @@ -0,0 +1,29 @@ +--- +name: action-recognition +description: "Guidance for action recognition in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving action recognition, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Action Recognition + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for action recognition. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on action recognition. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/action-recognition/agents/openai.yaml b/skills/action-recognition/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..2df40f8c6d870979bccad38d715a24d81417aa02 --- /dev/null +++ b/skills/action-recognition/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Action Recognition" +short_description: "Work on action recognition for Computer Vision." +default_prompt: "Use this skill to help with action recognition in Computer Vision." diff --git a/skills/active-learning/SKILL.md b/skills/active-learning/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..c7baa0be8f6ed3aa9df32dea9f66e453d158a7d9 --- /dev/null +++ b/skills/active-learning/SKILL.md @@ -0,0 +1,29 @@ +--- +name: active-learning +description: "Guidance for active learning in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving active learning, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Active Learning + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for active learning. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on active learning. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/active-learning/agents/openai.yaml b/skills/active-learning/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..1cc85fa8bc423ea6097e9c72f786b3df50a88530 --- /dev/null +++ b/skills/active-learning/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Active Learning" +short_description: "Work on active learning for Machine Learning." +default_prompt: "Use this skill to help with active learning in Machine Learning." diff --git a/skills/admin-dashboards/SKILL.md b/skills/admin-dashboards/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..232976d6c36f5f3d6120b75573b7f62f796efe80 --- /dev/null +++ b/skills/admin-dashboards/SKILL.md @@ -0,0 +1,29 @@ +--- +name: admin-dashboards +description: "Guidance for admin dashboards in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving admin dashboards, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Admin Dashboards + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for admin dashboards. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on admin dashboards. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/admin-dashboards/agents/openai.yaml b/skills/admin-dashboards/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..c13ebedbe129d624a03dc4678a4f75bd725d1591 --- /dev/null +++ b/skills/admin-dashboards/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Admin Dashboards" +short_description: "Work on admin dashboards for Web Engineering." +default_prompt: "Use this skill to help with admin dashboards in Web Engineering." diff --git a/skills/adversarial-prompt-tests/SKILL.md b/skills/adversarial-prompt-tests/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..d92fed6ff36b5f45866add91d96ef31f1e5d42b7 --- /dev/null +++ b/skills/adversarial-prompt-tests/SKILL.md @@ -0,0 +1,29 @@ +--- +name: adversarial-prompt-tests +description: "Guidance for adversarial prompt tests in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving adversarial prompt tests, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# Adversarial Prompt Tests + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for adversarial prompt tests. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on adversarial prompt tests. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/adversarial-prompt-tests/agents/openai.yaml b/skills/adversarial-prompt-tests/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d6609faf2e4501a7920c130af1d745733c069e12 --- /dev/null +++ b/skills/adversarial-prompt-tests/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Adversarial Prompt Tests" +short_description: "Work on adversarial prompt tests for Prompting And Evaluation." +default_prompt: "Use this skill to help with adversarial prompt tests in Prompting And Evaluation." diff --git a/skills/agent-evaluation-harnesses/SKILL.md b/skills/agent-evaluation-harnesses/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..e3436ad777f9312470dcbabfb734a15f8fae3e1f --- /dev/null +++ b/skills/agent-evaluation-harnesses/SKILL.md @@ -0,0 +1,29 @@ +--- +name: agent-evaluation-harnesses +description: "Guidance for agent evaluation harnesses in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving agent evaluation harnesses, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Agent Evaluation Harnesses + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for agent evaluation harnesses. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on agent evaluation harnesses. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/agent-evaluation-harnesses/agents/openai.yaml b/skills/agent-evaluation-harnesses/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7e2bf84461efeaf727d795acd134022259622506 --- /dev/null +++ b/skills/agent-evaluation-harnesses/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Agent Evaluation Harnesses" +short_description: "Work on agent evaluation harnesses for Agentic AI." +default_prompt: "Use this skill to help with agent evaluation harnesses in Agentic AI." diff --git a/skills/agent-memory-stores/SKILL.md b/skills/agent-memory-stores/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..81fc2dc618d23f94a7e8a2a9d7094fd9f5ede717 --- /dev/null +++ b/skills/agent-memory-stores/SKILL.md @@ -0,0 +1,29 @@ +--- +name: agent-memory-stores +description: "Guidance for agent memory stores in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving agent memory stores, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Agent Memory Stores + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for agent memory stores. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on agent memory stores. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/agent-memory-stores/agents/openai.yaml b/skills/agent-memory-stores/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..45d691e0463805122481689bd8930eccb00df8df --- /dev/null +++ b/skills/agent-memory-stores/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Agent Memory Stores" +short_description: "Work on agent memory stores for Agentic AI." +default_prompt: "Use this skill to help with agent memory stores in Agentic AI." diff --git a/skills/agent-trace-analysis/SKILL.md b/skills/agent-trace-analysis/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..5446cdbe612e0466876ec041b8d2dabcdd06a56b --- /dev/null +++ b/skills/agent-trace-analysis/SKILL.md @@ -0,0 +1,29 @@ +--- +name: agent-trace-analysis +description: "Guidance for agent trace analysis in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving agent trace analysis, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Agent Trace Analysis + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for agent trace analysis. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on agent trace analysis. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/agent-trace-analysis/agents/openai.yaml b/skills/agent-trace-analysis/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d0787b3ea035f95f70a04802f82207262f446379 --- /dev/null +++ b/skills/agent-trace-analysis/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Agent Trace Analysis" +short_description: "Work on agent trace analysis for Agentic AI." +default_prompt: "Use this skill to help with agent trace analysis in Agentic AI." diff --git a/skills/agriculture-ai-workflows/SKILL.md b/skills/agriculture-ai-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..e8b8fdffb990c7b5d26e502b27f108b91fe64d9c --- /dev/null +++ b/skills/agriculture-ai-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: agriculture-ai-workflows +description: "Guidance for agriculture AI workflows in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving agriculture AI workflows, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Agriculture AI Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for agriculture AI workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on agriculture AI workflows. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/agriculture-ai-workflows/agents/openai.yaml b/skills/agriculture-ai-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e865bf6d5966ab0ef3700bdd461ea3f5ac10e1f9 --- /dev/null +++ b/skills/agriculture-ai-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Agriculture AI Workflows" +short_description: "Work on agriculture AI workflows for Domain AI." +default_prompt: "Use this skill to help with agriculture AI workflows in Domain AI." diff --git a/skills/ai-admin-controls/SKILL.md b/skills/ai-admin-controls/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..fd1819f38c2f08c3b8304b3ba39013cf69c64a19 --- /dev/null +++ b/skills/ai-admin-controls/SKILL.md @@ -0,0 +1,29 @@ +--- +name: ai-admin-controls +description: "Guidance for AI admin controls in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving AI admin controls, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# AI Admin Controls + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for AI admin controls. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on AI admin controls. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/ai-admin-controls/agents/openai.yaml b/skills/ai-admin-controls/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..bba11c9feadbf2fdea685ee2c7f334a616cd987b --- /dev/null +++ b/skills/ai-admin-controls/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "AI Admin Controls" +short_description: "Work on AI admin controls for AI Product And UX." +default_prompt: "Use this skill to help with AI admin controls in AI Product And UX." diff --git a/skills/ai-collaboration-features/SKILL.md b/skills/ai-collaboration-features/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..1f25be0e9afdb14445f69da77ed4721b1ea272cf --- /dev/null +++ b/skills/ai-collaboration-features/SKILL.md @@ -0,0 +1,29 @@ +--- +name: ai-collaboration-features +description: "Guidance for AI collaboration features in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving AI collaboration features, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# AI Collaboration Features + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for AI collaboration features. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on AI collaboration features. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/ai-collaboration-features/agents/openai.yaml b/skills/ai-collaboration-features/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9ea483f1be3ba0b5e97c55a5fb810fad446f928a --- /dev/null +++ b/skills/ai-collaboration-features/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "AI Collaboration Features" +short_description: "Work on AI collaboration features for AI Product And UX." +default_prompt: "Use this skill to help with AI collaboration features in AI Product And UX." diff --git a/skills/ai-disclosure-copy/SKILL.md b/skills/ai-disclosure-copy/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..685b8ee970d8d3eeb4d706508366cfd8ee2b7805 --- /dev/null +++ b/skills/ai-disclosure-copy/SKILL.md @@ -0,0 +1,29 @@ +--- +name: ai-disclosure-copy +description: "Guidance for AI disclosure copy in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving AI disclosure copy, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# AI Disclosure Copy + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for AI disclosure copy. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on AI disclosure copy. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/ai-disclosure-copy/agents/openai.yaml b/skills/ai-disclosure-copy/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..dff7660edd7689dea10f85a49953ab0475126094 --- /dev/null +++ b/skills/ai-disclosure-copy/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "AI Disclosure Copy" +short_description: "Work on AI disclosure copy for AI Product And UX." +default_prompt: "Use this skill to help with AI disclosure copy in AI Product And UX." diff --git a/skills/ai-feature-scoping/SKILL.md b/skills/ai-feature-scoping/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..b929e49107ab5d3bbff9c883411d836b934d1d00 --- /dev/null +++ b/skills/ai-feature-scoping/SKILL.md @@ -0,0 +1,29 @@ +--- +name: ai-feature-scoping +description: "Guidance for AI feature scoping in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving AI feature scoping, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# AI Feature Scoping + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for AI feature scoping. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on AI feature scoping. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/ai-feature-scoping/agents/openai.yaml b/skills/ai-feature-scoping/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..37faba5377c273d34c6048729e69ce8beafda90b --- /dev/null +++ b/skills/ai-feature-scoping/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "AI Feature Scoping" +short_description: "Work on AI feature scoping for AI Product And UX." +default_prompt: "Use this skill to help with AI feature scoping in AI Product And UX." diff --git a/skills/ai-productivity-tools/SKILL.md b/skills/ai-productivity-tools/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..99d84a7a8d97463e930bf412b6324eb6917a07a6 --- /dev/null +++ b/skills/ai-productivity-tools/SKILL.md @@ -0,0 +1,29 @@ +--- +name: ai-productivity-tools +description: "Guidance for AI productivity tools in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving AI productivity tools, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# AI Productivity Tools + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for AI productivity tools. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on AI productivity tools. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/ai-productivity-tools/agents/openai.yaml b/skills/ai-productivity-tools/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..51420b14beaf026e95e0ffe65b42e2237192f67e --- /dev/null +++ b/skills/ai-productivity-tools/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "AI Productivity Tools" +short_description: "Work on AI productivity tools for AI Product And UX." +default_prompt: "Use this skill to help with AI productivity tools in AI Product And UX." diff --git a/skills/ai-safety-policy/SKILL.md b/skills/ai-safety-policy/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..8bddfda9ac542bb4f8b08e82db4f5c56e218ae43 --- /dev/null +++ b/skills/ai-safety-policy/SKILL.md @@ -0,0 +1,29 @@ +--- +name: ai-safety-policy +description: "Guidance for AI safety policy in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving AI safety policy, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# AI Safety Policy + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for AI safety policy. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on AI safety policy. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/ai-safety-policy/agents/openai.yaml b/skills/ai-safety-policy/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..024423c65164a8bc37480dd8780d385325e3d0d6 --- /dev/null +++ b/skills/ai-safety-policy/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "AI Safety Policy" +short_description: "Work on AI safety policy for Security And Privacy." +default_prompt: "Use this skill to help with AI safety policy in Security And Privacy." diff --git a/skills/ai-settings-panels/SKILL.md b/skills/ai-settings-panels/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..bd1875a5f3c145af631a725bdf9fb4b6d3e28f00 --- /dev/null +++ b/skills/ai-settings-panels/SKILL.md @@ -0,0 +1,29 @@ +--- +name: ai-settings-panels +description: "Guidance for AI settings panels in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving AI settings panels, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# AI Settings Panels + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for AI settings panels. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on AI settings panels. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/ai-settings-panels/agents/openai.yaml b/skills/ai-settings-panels/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..f1ccabb94595d63732ac5bb17da63ca2ecfa7823 --- /dev/null +++ b/skills/ai-settings-panels/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "AI Settings Panels" +short_description: "Work on AI settings panels for AI Product And UX." +default_prompt: "Use this skill to help with AI settings panels in AI Product And UX." diff --git a/skills/ai-user-onboarding/SKILL.md b/skills/ai-user-onboarding/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..5d188133e9acd08ec593e25a1b8eb1e1b6f87670 --- /dev/null +++ b/skills/ai-user-onboarding/SKILL.md @@ -0,0 +1,29 @@ +--- +name: ai-user-onboarding +description: "Guidance for AI user onboarding in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving AI user onboarding, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# AI User Onboarding + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for AI user onboarding. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on AI user onboarding. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/ai-user-onboarding/agents/openai.yaml b/skills/ai-user-onboarding/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..083fb0506f60f14cd93998a1e9aa5100b3efb851 --- /dev/null +++ b/skills/ai-user-onboarding/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "AI User Onboarding" +short_description: "Work on AI user onboarding for AI Product And UX." +default_prompt: "Use this skill to help with AI user onboarding in AI Product And UX." diff --git a/skills/analytics-event-schemas/SKILL.md b/skills/analytics-event-schemas/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..dcf54000b843acae8051d400f3a3ff3c2926cdb7 --- /dev/null +++ b/skills/analytics-event-schemas/SKILL.md @@ -0,0 +1,29 @@ +--- +name: analytics-event-schemas +description: "Guidance for analytics event schemas in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving analytics event schemas, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# Analytics Event Schemas + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for analytics event schemas. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on analytics event schemas. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/analytics-event-schemas/agents/openai.yaml b/skills/analytics-event-schemas/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3aaeca2659c7198d87afe675bb5e45e43a3ae959 --- /dev/null +++ b/skills/analytics-event-schemas/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Analytics Event Schemas" +short_description: "Work on analytics event schemas for Databases And Analytics." +default_prompt: "Use this skill to help with analytics event schemas in Databases And Analytics." diff --git a/skills/android-kotlin-apps/SKILL.md b/skills/android-kotlin-apps/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..8e52ff58204669cc36c27a1e81bbed9030f946fa --- /dev/null +++ b/skills/android-kotlin-apps/SKILL.md @@ -0,0 +1,29 @@ +--- +name: android-kotlin-apps +description: "Guidance for Android Kotlin apps in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving Android Kotlin apps, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Android Kotlin Apps + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for Android Kotlin apps. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on Android Kotlin apps. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/android-kotlin-apps/agents/openai.yaml b/skills/android-kotlin-apps/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e891c87a95871cd84606e6e19517817a53405f62 --- /dev/null +++ b/skills/android-kotlin-apps/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Android Kotlin Apps" +short_description: "Work on Android Kotlin apps for Mobile App Engineering." +default_prompt: "Use this skill to help with Android Kotlin apps in Mobile App Engineering." diff --git a/skills/annotation-workflows/SKILL.md b/skills/annotation-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..972ef3d85ec4302ba243cd297aafc27bdd0547dd --- /dev/null +++ b/skills/annotation-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: annotation-workflows +description: "Guidance for annotation workflows in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving annotation workflows, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# Annotation Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for annotation workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on annotation workflows. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/annotation-workflows/agents/openai.yaml b/skills/annotation-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..c26626747cef61308351c547ff089e981b0cd492 --- /dev/null +++ b/skills/annotation-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Annotation Workflows" +short_description: "Work on annotation workflows for AI Product And UX." +default_prompt: "Use this skill to help with annotation workflows in AI Product And UX." diff --git a/skills/anomaly-detection/SKILL.md b/skills/anomaly-detection/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..86cedfcdac96c8d9a737678a4faa10bfd64f2a8f --- /dev/null +++ b/skills/anomaly-detection/SKILL.md @@ -0,0 +1,29 @@ +--- +name: anomaly-detection +description: "Guidance for anomaly detection in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving anomaly detection, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Anomaly Detection + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for anomaly detection. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on anomaly detection. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/anomaly-detection/agents/openai.yaml b/skills/anomaly-detection/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..acb79ac73de298d85ade2ff0d654ff7ee0bbce3e --- /dev/null +++ b/skills/anomaly-detection/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Anomaly Detection" +short_description: "Work on anomaly detection for Machine Learning." +default_prompt: "Use this skill to help with anomaly detection in Machine Learning." diff --git a/skills/answer-citation-checks/SKILL.md b/skills/answer-citation-checks/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..6675180ff13331020dab08c743aa574ed2c6569f --- /dev/null +++ b/skills/answer-citation-checks/SKILL.md @@ -0,0 +1,29 @@ +--- +name: answer-citation-checks +description: "Guidance for answer citation checks in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving answer citation checks, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# Answer Citation Checks + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for answer citation checks. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on answer citation checks. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/answer-citation-checks/agents/openai.yaml b/skills/answer-citation-checks/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..65df02acb7341be2e41cc04754ea45cb84713991 --- /dev/null +++ b/skills/answer-citation-checks/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Answer Citation Checks" +short_description: "Work on answer citation checks for Prompting And Evaluation." +default_prompt: "Use this skill to help with answer citation checks in Prompting And Evaluation." diff --git a/skills/api-abuse-prevention/SKILL.md b/skills/api-abuse-prevention/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..10ce4b318bfec664aa6c9d1d56d02e068dc8233a --- /dev/null +++ b/skills/api-abuse-prevention/SKILL.md @@ -0,0 +1,29 @@ +--- +name: api-abuse-prevention +description: "Guidance for API abuse prevention in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving API abuse prevention, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# API Abuse Prevention + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for API abuse prevention. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on API abuse prevention. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/api-abuse-prevention/agents/openai.yaml b/skills/api-abuse-prevention/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..cf97f014901d4ef67bb51f9299542c529b7a4182 --- /dev/null +++ b/skills/api-abuse-prevention/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "API Abuse Prevention" +short_description: "Work on API abuse prevention for Security And Privacy." +default_prompt: "Use this skill to help with API abuse prevention in Security And Privacy." diff --git a/skills/api-latency-optimization/SKILL.md b/skills/api-latency-optimization/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..f6f5803e8bfeb067d9aca50fc55dd3576be5e1a6 --- /dev/null +++ b/skills/api-latency-optimization/SKILL.md @@ -0,0 +1,29 @@ +--- +name: api-latency-optimization +description: "Guidance for API latency optimization in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving API latency optimization, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# API Latency Optimization + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for API latency optimization. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on API latency optimization. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/api-latency-optimization/agents/openai.yaml b/skills/api-latency-optimization/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..86c7164f21b2eced88895e25b2ddcdc515730838 --- /dev/null +++ b/skills/api-latency-optimization/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "API Latency Optimization" +short_description: "Work on API latency optimization for LLM Engineering." +default_prompt: "Use this skill to help with API latency optimization in LLM Engineering." diff --git a/skills/api-route-design/SKILL.md b/skills/api-route-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..aac6d3d3def030280ab5e1e7fdbfb97b66b8d100 --- /dev/null +++ b/skills/api-route-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: api-route-design +description: "Guidance for API route design in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving API route design, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# API Route Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for API route design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on API route design. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/api-route-design/agents/openai.yaml b/skills/api-route-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..33ce4cdf8ffa6ebdf37dc719a4deb0a222c8f2b7 --- /dev/null +++ b/skills/api-route-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "API Route Design" +short_description: "Work on API route design for Web Engineering." +default_prompt: "Use this skill to help with API route design in Web Engineering." diff --git a/skills/app-store-readiness/SKILL.md b/skills/app-store-readiness/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..0d5591cd65b504cc5d19b15fdb8b84b891778dae --- /dev/null +++ b/skills/app-store-readiness/SKILL.md @@ -0,0 +1,29 @@ +--- +name: app-store-readiness +description: "Guidance for app store readiness in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving app store readiness, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# App Store Readiness + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for app store readiness. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on app store readiness. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/app-store-readiness/agents/openai.yaml b/skills/app-store-readiness/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b578738ea81dbb459da0cd03e2b15ffc5b36a83f --- /dev/null +++ b/skills/app-store-readiness/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "App Store Readiness" +short_description: "Work on app store readiness for Mobile App Engineering." +default_prompt: "Use this skill to help with app store readiness in Mobile App Engineering." diff --git a/skills/approval-gated-actions/SKILL.md b/skills/approval-gated-actions/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..6269263c6e100f06838bcd81129e0bd2ce28c194 --- /dev/null +++ b/skills/approval-gated-actions/SKILL.md @@ -0,0 +1,29 @@ +--- +name: approval-gated-actions +description: "Guidance for approval gated actions in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving approval gated actions, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Approval Gated Actions + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for approval gated actions. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on approval gated actions. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/approval-gated-actions/agents/openai.yaml b/skills/approval-gated-actions/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..a226fdec6083e69797415edd4e28d128fc0fb861 --- /dev/null +++ b/skills/approval-gated-actions/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Approval Gated Actions" +short_description: "Work on approval gated actions for Agentic AI." +default_prompt: "Use this skill to help with approval gated actions in Agentic AI." diff --git a/skills/artifact-promotion/SKILL.md b/skills/artifact-promotion/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..86cd9d564f93d91c5bc2f3e4ffda3879a7dba26b --- /dev/null +++ b/skills/artifact-promotion/SKILL.md @@ -0,0 +1,29 @@ +--- +name: artifact-promotion +description: "Guidance for artifact promotion in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving artifact promotion, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# Artifact Promotion + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for artifact promotion. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on artifact promotion. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/artifact-promotion/agents/openai.yaml b/skills/artifact-promotion/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..5bfc57dbddc4c66fa8421547ff4ec2dff03991a0 --- /dev/null +++ b/skills/artifact-promotion/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Artifact Promotion" +short_description: "Work on artifact promotion for Cloud And DevOps." +default_prompt: "Use this skill to help with artifact promotion in Cloud And DevOps." diff --git a/skills/attention-mechanisms/SKILL.md b/skills/attention-mechanisms/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..0cb7d11f1f10196471e7c2bb67308b0f9a97115d --- /dev/null +++ b/skills/attention-mechanisms/SKILL.md @@ -0,0 +1,29 @@ +--- +name: attention-mechanisms +description: "Guidance for attention mechanisms in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving attention mechanisms, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Attention Mechanisms + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for attention mechanisms. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on attention mechanisms. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/attention-mechanisms/agents/openai.yaml b/skills/attention-mechanisms/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..82cf9a39ca2d818a45c95dadb53d96bca2abf3f4 --- /dev/null +++ b/skills/attention-mechanisms/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Attention Mechanisms" +short_description: "Work on attention mechanisms for Deep Learning." +default_prompt: "Use this skill to help with attention mechanisms in Deep Learning." diff --git a/skills/audio-classification/SKILL.md b/skills/audio-classification/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..72b9629f557d08b55568a01c94bd96f8c4786c23 --- /dev/null +++ b/skills/audio-classification/SKILL.md @@ -0,0 +1,29 @@ +--- +name: audio-classification +description: "Guidance for audio classification in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving audio classification, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Audio Classification + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for audio classification. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on audio classification. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/audio-classification/agents/openai.yaml b/skills/audio-classification/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b1f5b568f436f9e75411bd7152d63c5d1787403f --- /dev/null +++ b/skills/audio-classification/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Audio Classification" +short_description: "Work on audio classification for Speech And Audio." +default_prompt: "Use this skill to help with audio classification in Speech And Audio." diff --git a/skills/audio-dataset-curation/SKILL.md b/skills/audio-dataset-curation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..cc4fe49a59cba0dd1c08e4b34118bed03e864a47 --- /dev/null +++ b/skills/audio-dataset-curation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: audio-dataset-curation +description: "Guidance for audio dataset curation in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving audio dataset curation, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Audio Dataset Curation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for audio dataset curation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on audio dataset curation. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/audio-dataset-curation/agents/openai.yaml b/skills/audio-dataset-curation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..4341344b1508708cbbf24a3fec55994dd17d463f --- /dev/null +++ b/skills/audio-dataset-curation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Audio Dataset Curation" +short_description: "Work on audio dataset curation for Speech And Audio." +default_prompt: "Use this skill to help with audio dataset curation in Speech And Audio." diff --git a/skills/audio-denoising/SKILL.md b/skills/audio-denoising/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..844d4936a738491bcf8e1766a4477b0542808a57 --- /dev/null +++ b/skills/audio-denoising/SKILL.md @@ -0,0 +1,29 @@ +--- +name: audio-denoising +description: "Guidance for audio denoising in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving audio denoising, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Audio Denoising + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for audio denoising. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on audio denoising. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/audio-denoising/agents/openai.yaml b/skills/audio-denoising/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..129fcc12afee9cb4ee0719320d9be1c8475b1c0a --- /dev/null +++ b/skills/audio-denoising/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Audio Denoising" +short_description: "Work on audio denoising for Speech And Audio." +default_prompt: "Use this skill to help with audio denoising in Speech And Audio." diff --git a/skills/audio-feature-extraction/SKILL.md b/skills/audio-feature-extraction/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..888c7966b5e2f07a8c380bd9d52d0d4fd94cdee2 --- /dev/null +++ b/skills/audio-feature-extraction/SKILL.md @@ -0,0 +1,29 @@ +--- +name: audio-feature-extraction +description: "Guidance for audio feature extraction in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving audio feature extraction, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Audio Feature Extraction + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for audio feature extraction. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on audio feature extraction. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/audio-feature-extraction/agents/openai.yaml b/skills/audio-feature-extraction/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9de7b780ecd5cf969c5e05c0a5ba949af5f0113f --- /dev/null +++ b/skills/audio-feature-extraction/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Audio Feature Extraction" +short_description: "Work on audio feature extraction for Speech And Audio." +default_prompt: "Use this skill to help with audio feature extraction in Speech And Audio." diff --git a/skills/audio-visual-fusion/SKILL.md b/skills/audio-visual-fusion/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..ff7ac60eb7401cd875c6b3c3b9bce73f47858d9a --- /dev/null +++ b/skills/audio-visual-fusion/SKILL.md @@ -0,0 +1,29 @@ +--- +name: audio-visual-fusion +description: "Guidance for audio visual fusion in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving audio visual fusion, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Audio Visual Fusion + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for audio visual fusion. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on audio visual fusion. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/audio-visual-fusion/agents/openai.yaml b/skills/audio-visual-fusion/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..5de8ef0be8221936328ed0679171b90352313e5d --- /dev/null +++ b/skills/audio-visual-fusion/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Audio Visual Fusion" +short_description: "Work on audio visual fusion for Multimodal AI." +default_prompt: "Use this skill to help with audio visual fusion in Multimodal AI." diff --git a/skills/audit-logging/SKILL.md b/skills/audit-logging/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..c54e22d3882449abeb680e6cd47ab2a2470fbca5 --- /dev/null +++ b/skills/audit-logging/SKILL.md @@ -0,0 +1,29 @@ +--- +name: audit-logging +description: "Guidance for audit logging in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving audit logging, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# Audit Logging + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for audit logging. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on audit logging. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/audit-logging/agents/openai.yaml b/skills/audit-logging/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..2a52697cd123f5bea963c9a40cede86b6020280a --- /dev/null +++ b/skills/audit-logging/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Audit Logging" +short_description: "Work on audit logging for Security And Privacy." +default_prompt: "Use this skill to help with audit logging in Security And Privacy." diff --git a/skills/authentication-flows/SKILL.md b/skills/authentication-flows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..8d2712c77e2c12082b7779e477f3d5784470d783 --- /dev/null +++ b/skills/authentication-flows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: authentication-flows +description: "Guidance for authentication flows in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving authentication flows, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Authentication Flows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for authentication flows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on authentication flows. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/authentication-flows/agents/openai.yaml b/skills/authentication-flows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..60e685f50b29676aa77058292fa1ef6665844658 --- /dev/null +++ b/skills/authentication-flows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Authentication Flows" +short_description: "Work on authentication flows for Web Engineering." +default_prompt: "Use this skill to help with authentication flows in Web Engineering." diff --git a/skills/authentication-security/SKILL.md b/skills/authentication-security/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..543586ba5247ac07c69f908bce8328b4ab155f1c --- /dev/null +++ b/skills/authentication-security/SKILL.md @@ -0,0 +1,29 @@ +--- +name: authentication-security +description: "Guidance for authentication security in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving authentication security, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# Authentication Security + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for authentication security. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on authentication security. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/authentication-security/agents/openai.yaml b/skills/authentication-security/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7f7b2bdeec702926acd3cee3d968f0c01477c1d3 --- /dev/null +++ b/skills/authentication-security/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Authentication Security" +short_description: "Work on authentication security for Security And Privacy." +default_prompt: "Use this skill to help with authentication security in Security And Privacy." diff --git a/skills/authorization-security/SKILL.md b/skills/authorization-security/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..072fc79096e9c3d5da848f7c0e7459354b477490 --- /dev/null +++ b/skills/authorization-security/SKILL.md @@ -0,0 +1,29 @@ +--- +name: authorization-security +description: "Guidance for authorization security in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving authorization security, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# Authorization Security + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for authorization security. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on authorization security. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/authorization-security/agents/openai.yaml b/skills/authorization-security/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..354d0ecbbcf1c2a1c0f919435c35d33bbd9c3532 --- /dev/null +++ b/skills/authorization-security/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Authorization Security" +short_description: "Work on authorization security for Security And Privacy." +default_prompt: "Use this skill to help with authorization security in Security And Privacy." diff --git a/skills/authorization-ui/SKILL.md b/skills/authorization-ui/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..325933bdff456c2834f67d66178f42c2a4ae0933 --- /dev/null +++ b/skills/authorization-ui/SKILL.md @@ -0,0 +1,29 @@ +--- +name: authorization-ui +description: "Guidance for authorization UI in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving authorization UI, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Authorization UI + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for authorization UI. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on authorization UI. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/authorization-ui/agents/openai.yaml b/skills/authorization-ui/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..fcaff76d7437bf534def6c2c1c8e0cca150fc191 --- /dev/null +++ b/skills/authorization-ui/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Authorization UI" +short_description: "Work on authorization UI for Web Engineering." +default_prompt: "Use this skill to help with authorization UI in Web Engineering." diff --git a/skills/autoencoders/SKILL.md b/skills/autoencoders/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..88b6edb2cc4c424b28ff3289e87ebde2662363e0 --- /dev/null +++ b/skills/autoencoders/SKILL.md @@ -0,0 +1,29 @@ +--- +name: autoencoders +description: "Guidance for autoencoders in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving autoencoders, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Autoencoders + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for autoencoders. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on autoencoders. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/autoencoders/agents/openai.yaml b/skills/autoencoders/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..f14de1094622e3102555d0fcc163bf5994b0c817 --- /dev/null +++ b/skills/autoencoders/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Autoencoders" +short_description: "Work on autoencoders for Deep Learning." +default_prompt: "Use this skill to help with autoencoders in Deep Learning." diff --git a/skills/autonomous-navigation/SKILL.md b/skills/autonomous-navigation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..e893da40d89c5caa63cf16ca7ae647202949569a --- /dev/null +++ b/skills/autonomous-navigation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: autonomous-navigation +description: "Guidance for autonomous navigation in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving autonomous navigation, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# Autonomous Navigation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for autonomous navigation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on autonomous navigation. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/autonomous-navigation/agents/openai.yaml b/skills/autonomous-navigation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..0fec69fbf865c9db3d632b9c523527018ee62499 --- /dev/null +++ b/skills/autonomous-navigation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Autonomous Navigation" +short_description: "Work on autonomous navigation for Robotics And IoT." +default_prompt: "Use this skill to help with autonomous navigation in Robotics And IoT." diff --git a/skills/autonomous-retry-policy/SKILL.md b/skills/autonomous-retry-policy/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..ad3a52427ed13c05499496b2dd1c65025a6e5016 --- /dev/null +++ b/skills/autonomous-retry-policy/SKILL.md @@ -0,0 +1,29 @@ +--- +name: autonomous-retry-policy +description: "Guidance for autonomous retry policy in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving autonomous retry policy, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Autonomous Retry Policy + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for autonomous retry policy. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on autonomous retry policy. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/autonomous-retry-policy/agents/openai.yaml b/skills/autonomous-retry-policy/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..22059ce929581907f57b7a727e367dd98e06fdb7 --- /dev/null +++ b/skills/autonomous-retry-policy/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Autonomous Retry Policy" +short_description: "Work on autonomous retry policy for Agentic AI." +default_prompt: "Use this skill to help with autonomous retry policy in Agentic AI." diff --git a/skills/autoscaling-design/SKILL.md b/skills/autoscaling-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..fa501011c6119a5816b8836eb4988e57ef013fad --- /dev/null +++ b/skills/autoscaling-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: autoscaling-design +description: "Guidance for autoscaling design in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving autoscaling design, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# Autoscaling Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for autoscaling design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on autoscaling design. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/autoscaling-design/agents/openai.yaml b/skills/autoscaling-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..109f9ae12715343749bdbd2b0d35dad4bcbde1f5 --- /dev/null +++ b/skills/autoscaling-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Autoscaling Design" +short_description: "Work on autoscaling design for Cloud And DevOps." +default_prompt: "Use this skill to help with autoscaling design in Cloud And DevOps." diff --git a/skills/background-sync/SKILL.md b/skills/background-sync/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..4ebb8c49a4fee6aefe2632c6744f48f197ad05ef --- /dev/null +++ b/skills/background-sync/SKILL.md @@ -0,0 +1,29 @@ +--- +name: background-sync +description: "Guidance for background sync in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving background sync, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Background Sync + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for background sync. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on background sync. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/background-sync/agents/openai.yaml b/skills/background-sync/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..235642313aae4093ecb79850c0520e9bccb0fb28 --- /dev/null +++ b/skills/background-sync/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Background Sync" +short_description: "Work on background sync for Mobile App Engineering." +default_prompt: "Use this skill to help with background sync in Mobile App Engineering." diff --git a/skills/backup-and-restore/SKILL.md b/skills/backup-and-restore/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..24552200c9e40f27c1e5898e353f9bb4f0a79e79 --- /dev/null +++ b/skills/backup-and-restore/SKILL.md @@ -0,0 +1,29 @@ +--- +name: backup-and-restore +description: "Guidance for backup and restore in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving backup and restore, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# Backup and Restore + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for backup and restore. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on backup and restore. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/backup-and-restore/agents/openai.yaml b/skills/backup-and-restore/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d7d1afed8fee6c2b400afa2ca1a00acc1e3e6678 --- /dev/null +++ b/skills/backup-and-restore/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Backup and Restore" +short_description: "Work on backup and restore for Cloud And DevOps." +default_prompt: "Use this skill to help with backup and restore in Cloud And DevOps." diff --git a/skills/backup-verification/SKILL.md b/skills/backup-verification/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..5f20c8bbad398e39c41a115d97847fd7665636b9 --- /dev/null +++ b/skills/backup-verification/SKILL.md @@ -0,0 +1,29 @@ +--- +name: backup-verification +description: "Guidance for backup verification in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving backup verification, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# Backup Verification + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for backup verification. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on backup verification. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/backup-verification/agents/openai.yaml b/skills/backup-verification/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..12c05c259d00dafca37be7d012b070459a57b7c3 --- /dev/null +++ b/skills/backup-verification/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Backup Verification" +short_description: "Work on backup verification for Databases And Analytics." +default_prompt: "Use this skill to help with backup verification in Databases And Analytics." diff --git a/skills/baseline-modeling/SKILL.md b/skills/baseline-modeling/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..c3c65e0ba59a1bf55d39229bd7f1944822a5f642 --- /dev/null +++ b/skills/baseline-modeling/SKILL.md @@ -0,0 +1,29 @@ +--- +name: baseline-modeling +description: "Guidance for baseline modeling in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving baseline modeling, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Baseline Modeling + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for baseline modeling. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on baseline modeling. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/baseline-modeling/agents/openai.yaml b/skills/baseline-modeling/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9fe915676b10ba073f8f804d7f0f8e7e795782f2 --- /dev/null +++ b/skills/baseline-modeling/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Baseline Modeling" +short_description: "Work on baseline modeling for Machine Learning." +default_prompt: "Use this skill to help with baseline modeling in Machine Learning." diff --git a/skills/batch-inference-jobs/SKILL.md b/skills/batch-inference-jobs/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..53c6712d75509068e943c755902c0d4691d80a6a --- /dev/null +++ b/skills/batch-inference-jobs/SKILL.md @@ -0,0 +1,29 @@ +--- +name: batch-inference-jobs +description: "Guidance for batch inference jobs in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving batch inference jobs, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# Batch Inference Jobs + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for batch inference jobs. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on batch inference jobs. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/batch-inference-jobs/agents/openai.yaml b/skills/batch-inference-jobs/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e6cce176f85b2e0a1207a871e93e7331b9fcc681 --- /dev/null +++ b/skills/batch-inference-jobs/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Batch Inference Jobs" +short_description: "Work on batch inference jobs for MLOps." +default_prompt: "Use this skill to help with batch inference jobs in MLOps." diff --git a/skills/batch-processing/SKILL.md b/skills/batch-processing/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..bacac8c01de6bb7eb0f286d9ec6a0b4e408cc843 --- /dev/null +++ b/skills/batch-processing/SKILL.md @@ -0,0 +1,29 @@ +--- +name: batch-processing +description: "Guidance for batch processing in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving batch processing, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Batch Processing + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for batch processing. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on batch processing. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/batch-processing/agents/openai.yaml b/skills/batch-processing/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..eaac19de0b27df993f5d000fd95071dc332d8852 --- /dev/null +++ b/skills/batch-processing/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Batch Processing" +short_description: "Work on batch processing for Data Engineering." +default_prompt: "Use this skill to help with batch processing in Data Engineering." diff --git a/skills/benchmark-suite-design/SKILL.md b/skills/benchmark-suite-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..7991af9f4cfc6cb54e4536c806d6b4b19aebbec3 --- /dev/null +++ b/skills/benchmark-suite-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: benchmark-suite-design +description: "Guidance for benchmark suite design in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving benchmark suite design, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Benchmark Suite Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for benchmark suite design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on benchmark suite design. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/benchmark-suite-design/agents/openai.yaml b/skills/benchmark-suite-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b6c1521bd3110abc9cb32f61c413cb11b8167b29 --- /dev/null +++ b/skills/benchmark-suite-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Benchmark Suite Design" +short_description: "Work on benchmark suite design for Research And Scientific AI." +default_prompt: "Use this skill to help with benchmark suite design in Research And Scientific AI." diff --git a/skills/bi-semantic-models/SKILL.md b/skills/bi-semantic-models/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..86842d145a6078b0b4e93bbab8a12f9078a94084 --- /dev/null +++ b/skills/bi-semantic-models/SKILL.md @@ -0,0 +1,29 @@ +--- +name: bi-semantic-models +description: "Guidance for BI semantic models in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving BI semantic models, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# BI Semantic Models + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for BI semantic models. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on BI semantic models. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/bi-semantic-models/agents/openai.yaml b/skills/bi-semantic-models/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9bf7cae97765d866061d342d302fe8b690bf616f --- /dev/null +++ b/skills/bi-semantic-models/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "BI Semantic Models" +short_description: "Work on BI semantic models for Data Engineering." +default_prompt: "Use this skill to help with BI semantic models in Data Engineering." diff --git a/skills/bias-evaluation/SKILL.md b/skills/bias-evaluation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..99b5bf7126d1486d0a1d04ea6dcb273ef3eecf8f --- /dev/null +++ b/skills/bias-evaluation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: bias-evaluation +description: "Guidance for bias evaluation in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving bias evaluation, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# Bias Evaluation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for bias evaluation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on bias evaluation. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/bias-evaluation/agents/openai.yaml b/skills/bias-evaluation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..dc90fcd30820b132f52892d75d157963e4450382 --- /dev/null +++ b/skills/bias-evaluation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Bias Evaluation" +short_description: "Work on bias evaluation for Prompting And Evaluation." +default_prompt: "Use this skill to help with bias evaluation in Prompting And Evaluation." diff --git a/skills/bioinformatics-ml/SKILL.md b/skills/bioinformatics-ml/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..d4918728ae1a8602abb4723de7bb0ea093ab313a --- /dev/null +++ b/skills/bioinformatics-ml/SKILL.md @@ -0,0 +1,29 @@ +--- +name: bioinformatics-ml +description: "Guidance for bioinformatics ML in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving bioinformatics ML, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Bioinformatics ML + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for bioinformatics ML. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on bioinformatics ML. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/bioinformatics-ml/agents/openai.yaml b/skills/bioinformatics-ml/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..8e9f51350d4dc02909171be5ff84bd6dc1a1cf3d --- /dev/null +++ b/skills/bioinformatics-ml/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Bioinformatics ML" +short_description: "Work on bioinformatics ML for Research And Scientific AI." +default_prompt: "Use this skill to help with bioinformatics ML in Research And Scientific AI." diff --git a/skills/blue-green-deploys/SKILL.md b/skills/blue-green-deploys/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..9e5be025be35f0065dab1930a0e7260518a3506a --- /dev/null +++ b/skills/blue-green-deploys/SKILL.md @@ -0,0 +1,29 @@ +--- +name: blue-green-deploys +description: "Guidance for blue green deploys in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving blue green deploys, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# Blue Green Deploys + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for blue green deploys. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on blue green deploys. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/blue-green-deploys/agents/openai.yaml b/skills/blue-green-deploys/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..46586992ecb5ff15a2a17cc46495026087b4b2e3 --- /dev/null +++ b/skills/blue-green-deploys/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Blue Green Deploys" +short_description: "Work on blue green deploys for Cloud And DevOps." +default_prompt: "Use this skill to help with blue green deploys in Cloud And DevOps." diff --git a/skills/browser-automation-agents/SKILL.md b/skills/browser-automation-agents/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..362c60385f45c78f28b943eb88f2ed09f46563d2 --- /dev/null +++ b/skills/browser-automation-agents/SKILL.md @@ -0,0 +1,29 @@ +--- +name: browser-automation-agents +description: "Guidance for browser automation agents in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving browser automation agents, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Browser Automation Agents + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for browser automation agents. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on browser automation agents. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/browser-automation-agents/agents/openai.yaml b/skills/browser-automation-agents/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..4f0c7ea6f6ddac0b445e9251f3dabf1c2f18c6b3 --- /dev/null +++ b/skills/browser-automation-agents/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Browser Automation Agents" +short_description: "Work on browser automation agents for Agentic AI." +default_prompt: "Use this skill to help with browser automation agents in Agentic AI." diff --git a/skills/browser-testing/SKILL.md b/skills/browser-testing/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..19d42e4af81821d58197f8be76fd2fb64f566d1f --- /dev/null +++ b/skills/browser-testing/SKILL.md @@ -0,0 +1,29 @@ +--- +name: browser-testing +description: "Guidance for browser testing in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving browser testing, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Browser Testing + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for browser testing. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on browser testing. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/browser-testing/agents/openai.yaml b/skills/browser-testing/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3240711d340d68c10cebec4f72fa661cff8bd713 --- /dev/null +++ b/skills/browser-testing/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Browser Testing" +short_description: "Work on browser testing for Web Engineering." +default_prompt: "Use this skill to help with browser testing in Web Engineering." diff --git a/skills/call-center-analytics/SKILL.md b/skills/call-center-analytics/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..cc15f07e0adddebdc1eb2cbfb455d1f0530b0955 --- /dev/null +++ b/skills/call-center-analytics/SKILL.md @@ -0,0 +1,29 @@ +--- +name: call-center-analytics +description: "Guidance for call center analytics in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving call center analytics, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Call Center Analytics + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for call center analytics. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on call center analytics. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/call-center-analytics/agents/openai.yaml b/skills/call-center-analytics/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..fd97043b745f266f9e72894651b4f73c9877fd3a --- /dev/null +++ b/skills/call-center-analytics/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Call Center Analytics" +short_description: "Work on call center analytics for Speech And Audio." +default_prompt: "Use this skill to help with call center analytics in Speech And Audio." diff --git a/skills/camera-calibration/SKILL.md b/skills/camera-calibration/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a7cda0b1b0b4e65dceab9193b29ef235579b172d --- /dev/null +++ b/skills/camera-calibration/SKILL.md @@ -0,0 +1,29 @@ +--- +name: camera-calibration +description: "Guidance for camera calibration in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving camera calibration, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Camera Calibration + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for camera calibration. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on camera calibration. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/camera-calibration/agents/openai.yaml b/skills/camera-calibration/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..10e9c4ff766e2dd4bfb06a5f90e24cd5a613dcc3 --- /dev/null +++ b/skills/camera-calibration/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Camera Calibration" +short_description: "Work on camera calibration for Computer Vision." +default_prompt: "Use this skill to help with camera calibration in Computer Vision." diff --git a/skills/camera-integrations/SKILL.md b/skills/camera-integrations/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..95bb702867453d0c67428726a9f3bcf76ef89d83 --- /dev/null +++ b/skills/camera-integrations/SKILL.md @@ -0,0 +1,29 @@ +--- +name: camera-integrations +description: "Guidance for camera integrations in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving camera integrations, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Camera Integrations + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for camera integrations. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on camera integrations. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/camera-integrations/agents/openai.yaml b/skills/camera-integrations/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e9b3be62cc7ea82b7912573d43f85f52b705028c --- /dev/null +++ b/skills/camera-integrations/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Camera Integrations" +short_description: "Work on camera integrations for Mobile App Engineering." +default_prompt: "Use this skill to help with camera integrations in Mobile App Engineering." diff --git a/skills/canary-releases/SKILL.md b/skills/canary-releases/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..ac3d3c1863f520ad4913a6c5b8735b86110e9176 --- /dev/null +++ b/skills/canary-releases/SKILL.md @@ -0,0 +1,29 @@ +--- +name: canary-releases +description: "Guidance for canary releases in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving canary releases, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# Canary Releases + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for canary releases. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on canary releases. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/canary-releases/agents/openai.yaml b/skills/canary-releases/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7c9d09cf669d4240f6a6576c91b659b06c2bab8a --- /dev/null +++ b/skills/canary-releases/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Canary Releases" +short_description: "Work on canary releases for MLOps." +default_prompt: "Use this skill to help with canary releases in MLOps." diff --git a/skills/caption-quality-review/SKILL.md b/skills/caption-quality-review/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..fe44782f1303eb63737fad355b0a18cd295391f5 --- /dev/null +++ b/skills/caption-quality-review/SKILL.md @@ -0,0 +1,29 @@ +--- +name: caption-quality-review +description: "Guidance for caption quality review in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving caption quality review, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Caption Quality Review + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for caption quality review. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on caption quality review. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/caption-quality-review/agents/openai.yaml b/skills/caption-quality-review/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..912ef0020954343754d478c6c347eb0e28ea3725 --- /dev/null +++ b/skills/caption-quality-review/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Caption Quality Review" +short_description: "Work on caption quality review for Multimodal AI." +default_prompt: "Use this skill to help with caption quality review in Multimodal AI." diff --git a/skills/causal-inference/SKILL.md b/skills/causal-inference/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..2eb5443b9d981d0efce45cc9148f82c9caa94077 --- /dev/null +++ b/skills/causal-inference/SKILL.md @@ -0,0 +1,29 @@ +--- +name: causal-inference +description: "Guidance for causal inference in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving causal inference, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Causal Inference + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for causal inference. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on causal inference. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/causal-inference/agents/openai.yaml b/skills/causal-inference/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..50c22221e9b5cabc0450462cbe4cab0c64520880 --- /dev/null +++ b/skills/causal-inference/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Causal Inference" +short_description: "Work on causal inference for Machine Learning." +default_prompt: "Use this skill to help with causal inference in Machine Learning." diff --git a/skills/cd-for-ml/SKILL.md b/skills/cd-for-ml/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..be3a1e5cbb5aed6219af4a76b46ab6f0248ebce1 --- /dev/null +++ b/skills/cd-for-ml/SKILL.md @@ -0,0 +1,29 @@ +--- +name: cd-for-ml +description: "Guidance for CD for ML in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving CD for ML, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# CD For ML + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for CD for ML. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on CD for ML. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/cd-for-ml/agents/openai.yaml b/skills/cd-for-ml/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..948469a6a1a92546134dbf2da9c401b2ea7c70c2 --- /dev/null +++ b/skills/cd-for-ml/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "CD For ML" +short_description: "Work on CD for ML for MLOps." +default_prompt: "Use this skill to help with CD for ML in MLOps." diff --git a/skills/cdc-ingestion/SKILL.md b/skills/cdc-ingestion/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..26f3d1f7e436e2b44000dacf8f027cd1b5f640e0 --- /dev/null +++ b/skills/cdc-ingestion/SKILL.md @@ -0,0 +1,29 @@ +--- +name: cdc-ingestion +description: "Guidance for CDC ingestion in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving CDC ingestion, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# CDC Ingestion + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for CDC ingestion. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on CDC ingestion. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/cdc-ingestion/agents/openai.yaml b/skills/cdc-ingestion/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3c049438d739ac711138e4f29382db449311a4b8 --- /dev/null +++ b/skills/cdc-ingestion/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "CDC Ingestion" +short_description: "Work on CDC ingestion for Data Engineering." +default_prompt: "Use this skill to help with CDC ingestion in Data Engineering." diff --git a/skills/cdn-configuration/SKILL.md b/skills/cdn-configuration/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..61622280539219710a504041c969ea211c127c1d --- /dev/null +++ b/skills/cdn-configuration/SKILL.md @@ -0,0 +1,29 @@ +--- +name: cdn-configuration +description: "Guidance for CDN configuration in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving CDN configuration, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# CDN Configuration + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for CDN configuration. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on CDN configuration. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/cdn-configuration/agents/openai.yaml b/skills/cdn-configuration/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7af7f530805cae8ea7b76f7d67c15965701c94ec --- /dev/null +++ b/skills/cdn-configuration/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "CDN Configuration" +short_description: "Work on CDN configuration for Cloud And DevOps." +default_prompt: "Use this skill to help with CDN configuration in Cloud And DevOps." diff --git a/skills/chain-of-thought-redaction/SKILL.md b/skills/chain-of-thought-redaction/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..522500ee9de94c061025fe13cada988dfa5bb59d --- /dev/null +++ b/skills/chain-of-thought-redaction/SKILL.md @@ -0,0 +1,29 @@ +--- +name: chain-of-thought-redaction +description: "Guidance for chain of thought redaction in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving chain of thought redaction, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# Chain Of Thought Redaction + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for chain of thought redaction. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on chain of thought redaction. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/chain-of-thought-redaction/agents/openai.yaml b/skills/chain-of-thought-redaction/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b9b3e62ab61a8ca0918ba0b036de8c5e0aaf368c --- /dev/null +++ b/skills/chain-of-thought-redaction/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Chain Of Thought Redaction" +short_description: "Work on chain of thought redaction for Prompting And Evaluation." +default_prompt: "Use this skill to help with chain of thought redaction in Prompting And Evaluation." diff --git a/skills/chart-understanding/SKILL.md b/skills/chart-understanding/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..0d49fd4f72f2621de117b130c332ce4868193324 --- /dev/null +++ b/skills/chart-understanding/SKILL.md @@ -0,0 +1,29 @@ +--- +name: chart-understanding +description: "Guidance for chart understanding in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving chart understanding, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Chart Understanding + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for chart understanding. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on chart understanding. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/chart-understanding/agents/openai.yaml b/skills/chart-understanding/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9f150cf5bf55a24d10aeb4e34624a4b0e2ba1fc1 --- /dev/null +++ b/skills/chart-understanding/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Chart Understanding" +short_description: "Work on chart understanding for Multimodal AI." +default_prompt: "Use this skill to help with chart understanding in Multimodal AI." diff --git a/skills/chat-completion-orchestration/SKILL.md b/skills/chat-completion-orchestration/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..fb57fb968d3eaa554429141c79435d606b0a4b30 --- /dev/null +++ b/skills/chat-completion-orchestration/SKILL.md @@ -0,0 +1,29 @@ +--- +name: chat-completion-orchestration +description: "Guidance for chat completion orchestration in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving chat completion orchestration, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Chat Completion Orchestration + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for chat completion orchestration. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on chat completion orchestration. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/chat-completion-orchestration/agents/openai.yaml b/skills/chat-completion-orchestration/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..27f72de7fe38505d998e3831f7a3fa86245fff66 --- /dev/null +++ b/skills/chat-completion-orchestration/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Chat Completion Orchestration" +short_description: "Work on chat completion orchestration for LLM Engineering." +default_prompt: "Use this skill to help with chat completion orchestration in LLM Engineering." diff --git a/skills/chat-ux-design/SKILL.md b/skills/chat-ux-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..c836fd83cfdd7033eb39bec8dac9e92692ec1fbb --- /dev/null +++ b/skills/chat-ux-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: chat-ux-design +description: "Guidance for chat UX design in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving chat UX design, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# Chat UX Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for chat UX design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on chat UX design. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/chat-ux-design/agents/openai.yaml b/skills/chat-ux-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3c8f748849789f424a4ef6c283bbce95230f838a --- /dev/null +++ b/skills/chat-ux-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Chat UX Design" +short_description: "Work on chat UX design for AI Product And UX." +default_prompt: "Use this skill to help with chat UX design in AI Product And UX." diff --git a/skills/checkpoint-management/SKILL.md b/skills/checkpoint-management/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..41a3825b1bc3dd6babe256442ea8f33fd54bb0df --- /dev/null +++ b/skills/checkpoint-management/SKILL.md @@ -0,0 +1,29 @@ +--- +name: checkpoint-management +description: "Guidance for checkpoint management in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving checkpoint management, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Checkpoint Management + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for checkpoint management. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on checkpoint management. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/checkpoint-management/agents/openai.yaml b/skills/checkpoint-management/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..a1ddf77b93c448777d8512cf544045b9b7536942 --- /dev/null +++ b/skills/checkpoint-management/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Checkpoint Management" +short_description: "Work on checkpoint management for Deep Learning." +default_prompt: "Use this skill to help with checkpoint management in Deep Learning." diff --git a/skills/chemistry-ml/SKILL.md b/skills/chemistry-ml/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..2bc49033eb55beca0b9703f95370dfab9ba740bd --- /dev/null +++ b/skills/chemistry-ml/SKILL.md @@ -0,0 +1,29 @@ +--- +name: chemistry-ml +description: "Guidance for chemistry ML in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving chemistry ML, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Chemistry ML + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for chemistry ML. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on chemistry ML. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/chemistry-ml/agents/openai.yaml b/skills/chemistry-ml/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..6fca0cdb04ec316d4a85ab1bfebac88039d079d6 --- /dev/null +++ b/skills/chemistry-ml/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Chemistry ML" +short_description: "Work on chemistry ML for Research And Scientific AI." +default_prompt: "Use this skill to help with chemistry ML in Research And Scientific AI." diff --git a/skills/ci-for-ml/SKILL.md b/skills/ci-for-ml/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..faaf56b87c44292cfa3c5535e02e65c88d1aa477 --- /dev/null +++ b/skills/ci-for-ml/SKILL.md @@ -0,0 +1,29 @@ +--- +name: ci-for-ml +description: "Guidance for CI for ML in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving CI for ML, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# CI For ML + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for CI for ML. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on CI for ML. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/ci-for-ml/agents/openai.yaml b/skills/ci-for-ml/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..52136d967d6b10d7ea8b2b78d59306f36ad9edad --- /dev/null +++ b/skills/ci-for-ml/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "CI For ML" +short_description: "Work on CI for ML for MLOps." +default_prompt: "Use this skill to help with CI for ML in MLOps." diff --git a/skills/ci-pipeline-design/SKILL.md b/skills/ci-pipeline-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..00f1660f9d0a473fb73de12edeef11699a61c4d5 --- /dev/null +++ b/skills/ci-pipeline-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: ci-pipeline-design +description: "Guidance for CI pipeline design in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving CI pipeline design, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# CI Pipeline Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for CI pipeline design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on CI pipeline design. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/ci-pipeline-design/agents/openai.yaml b/skills/ci-pipeline-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..0ebc21856fdc32de84d8aa713ff8c76489f1dbfb --- /dev/null +++ b/skills/ci-pipeline-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "CI Pipeline Design" +short_description: "Work on CI pipeline design for Cloud And DevOps." +default_prompt: "Use this skill to help with CI pipeline design in Cloud And DevOps." diff --git a/skills/citation-graph-analysis/SKILL.md b/skills/citation-graph-analysis/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..67c858a73b22f165f66f18db0df82289af308a54 --- /dev/null +++ b/skills/citation-graph-analysis/SKILL.md @@ -0,0 +1,29 @@ +--- +name: citation-graph-analysis +description: "Guidance for citation graph analysis in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving citation graph analysis, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Citation Graph Analysis + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for citation graph analysis. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on citation graph analysis. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/citation-graph-analysis/agents/openai.yaml b/skills/citation-graph-analysis/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d755416cd5dade40ed6d97286f8613a2a90b3e33 --- /dev/null +++ b/skills/citation-graph-analysis/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Citation Graph Analysis" +short_description: "Work on citation graph analysis for Research And Scientific AI." +default_prompt: "Use this skill to help with citation graph analysis in Research And Scientific AI." diff --git a/skills/class-imbalance-handling/SKILL.md b/skills/class-imbalance-handling/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..7df25826e30ba571f4f7d21813012dfd57ed548c --- /dev/null +++ b/skills/class-imbalance-handling/SKILL.md @@ -0,0 +1,29 @@ +--- +name: class-imbalance-handling +description: "Guidance for class imbalance handling in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving class imbalance handling, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Class Imbalance Handling + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for class imbalance handling. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on class imbalance handling. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/class-imbalance-handling/agents/openai.yaml b/skills/class-imbalance-handling/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..bfff64cb001dbad24b1a3d83d5252b9fef85f087 --- /dev/null +++ b/skills/class-imbalance-handling/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Class Imbalance Handling" +short_description: "Work on class imbalance handling for Machine Learning." +default_prompt: "Use this skill to help with class imbalance handling in Machine Learning." diff --git a/skills/climate-modeling-ml/SKILL.md b/skills/climate-modeling-ml/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..322dc739b536fc39cf0fca2f3a565998488e8e9d --- /dev/null +++ b/skills/climate-modeling-ml/SKILL.md @@ -0,0 +1,29 @@ +--- +name: climate-modeling-ml +description: "Guidance for climate modeling ML in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving climate modeling ML, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Climate Modeling ML + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for climate modeling ML. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on climate modeling ML. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/climate-modeling-ml/agents/openai.yaml b/skills/climate-modeling-ml/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3f001d0f52ca171a6236e99f4d3ee67e01a4e9b6 --- /dev/null +++ b/skills/climate-modeling-ml/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Climate Modeling ML" +short_description: "Work on climate modeling ML for Research And Scientific AI." +default_prompt: "Use this skill to help with climate modeling ML in Research And Scientific AI." diff --git a/skills/clinical-document-nlp/SKILL.md b/skills/clinical-document-nlp/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..e7ffeb6a354289ba40222389f81a771f64c862be --- /dev/null +++ b/skills/clinical-document-nlp/SKILL.md @@ -0,0 +1,29 @@ +--- +name: clinical-document-nlp +description: "Guidance for clinical document NLP in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving clinical document NLP, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Clinical Document NLP + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for clinical document NLP. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on clinical document NLP. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/clinical-document-nlp/agents/openai.yaml b/skills/clinical-document-nlp/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e01ab29f072560b0cb28ca8af16c0048de7b1175 --- /dev/null +++ b/skills/clinical-document-nlp/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Clinical Document NLP" +short_description: "Work on clinical document NLP for Natural Language Processing." +default_prompt: "Use this skill to help with clinical document NLP in Natural Language Processing." diff --git a/skills/cloud-cost-optimization/SKILL.md b/skills/cloud-cost-optimization/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..9983c1d16a817979de027a0ede67e505d620177a --- /dev/null +++ b/skills/cloud-cost-optimization/SKILL.md @@ -0,0 +1,29 @@ +--- +name: cloud-cost-optimization +description: "Guidance for cloud cost optimization in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving cloud cost optimization, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# Cloud Cost Optimization + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for cloud cost optimization. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on cloud cost optimization. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/cloud-cost-optimization/agents/openai.yaml b/skills/cloud-cost-optimization/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b8673b35b5c28f9749f39f3c20fa34e5f622c0d1 --- /dev/null +++ b/skills/cloud-cost-optimization/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Cloud Cost Optimization" +short_description: "Work on cloud cost optimization for Cloud And DevOps." +default_prompt: "Use this skill to help with cloud cost optimization in Cloud And DevOps." diff --git a/skills/clustering-workflows/SKILL.md b/skills/clustering-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..050b234330c7b7ed6311d34ab90b4b6d67bebbc5 --- /dev/null +++ b/skills/clustering-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: clustering-workflows +description: "Guidance for clustering workflows in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving clustering workflows, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Clustering Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for clustering workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on clustering workflows. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/clustering-workflows/agents/openai.yaml b/skills/clustering-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..fd655f400046b424d0a9c8be9d92b9f0938d4bb2 --- /dev/null +++ b/skills/clustering-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Clustering Workflows" +short_description: "Work on clustering workflows for Machine Learning." +default_prompt: "Use this skill to help with clustering workflows in Machine Learning." diff --git a/skills/cnn-model-design/SKILL.md b/skills/cnn-model-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..697e8a6d35908bbc4bf29cff9823218ec708134f --- /dev/null +++ b/skills/cnn-model-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: cnn-model-design +description: "Guidance for CNN model design in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving CNN model design, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# CNN Model Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for CNN model design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on CNN model design. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/cnn-model-design/agents/openai.yaml b/skills/cnn-model-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..577b3c8a2ed8347b4ee3e0d06994d3d7537c68e9 --- /dev/null +++ b/skills/cnn-model-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "CNN Model Design" +short_description: "Work on CNN model design for Deep Learning." +default_prompt: "Use this skill to help with CNN model design in Deep Learning." diff --git a/skills/coding-agent-workflows/SKILL.md b/skills/coding-agent-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..e611cf66fd7dd4f4c21b5761df6b4d839df2a3c5 --- /dev/null +++ b/skills/coding-agent-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: coding-agent-workflows +description: "Guidance for coding agent workflows in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving coding agent workflows, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Coding Agent Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for coding agent workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on coding agent workflows. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/coding-agent-workflows/agents/openai.yaml b/skills/coding-agent-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..620a5a3e66a8252de97e60131c09469ad0877f01 --- /dev/null +++ b/skills/coding-agent-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Coding Agent Workflows" +short_description: "Work on coding agent workflows for Agentic AI." +default_prompt: "Use this skill to help with coding agent workflows in Agentic AI." diff --git a/skills/cohort-analysis/SKILL.md b/skills/cohort-analysis/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..f6ca4e4df7ee86cc83006fa8e1dcb7ed86235472 --- /dev/null +++ b/skills/cohort-analysis/SKILL.md @@ -0,0 +1,29 @@ +--- +name: cohort-analysis +description: "Guidance for cohort analysis in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving cohort analysis, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# Cohort Analysis + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for cohort analysis. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on cohort analysis. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/cohort-analysis/agents/openai.yaml b/skills/cohort-analysis/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..011bc0338644a4b15f1657da5dcfd4a234a2b212 --- /dev/null +++ b/skills/cohort-analysis/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Cohort Analysis" +short_description: "Work on cohort analysis for Databases And Analytics." +default_prompt: "Use this skill to help with cohort analysis in Databases And Analytics." diff --git a/skills/compliance-ai/SKILL.md b/skills/compliance-ai/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..014fc7c0ddb47f571093a8abd5c4c0c71a7a8627 --- /dev/null +++ b/skills/compliance-ai/SKILL.md @@ -0,0 +1,29 @@ +--- +name: compliance-ai +description: "Guidance for compliance AI in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving compliance AI, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Compliance AI + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for compliance AI. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on compliance AI. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/compliance-ai/agents/openai.yaml b/skills/compliance-ai/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..846b6abd03fef73a70a53f6e03e56d0df6c944be --- /dev/null +++ b/skills/compliance-ai/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Compliance AI" +short_description: "Work on compliance AI for Domain AI." +default_prompt: "Use this skill to help with compliance AI in Domain AI." diff --git a/skills/compliance-evidence/SKILL.md b/skills/compliance-evidence/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..6eca690195558e103db97d0830c6f609cf6ee95c --- /dev/null +++ b/skills/compliance-evidence/SKILL.md @@ -0,0 +1,29 @@ +--- +name: compliance-evidence +description: "Guidance for compliance evidence in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving compliance evidence, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# Compliance Evidence + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for compliance evidence. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on compliance evidence. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/compliance-evidence/agents/openai.yaml b/skills/compliance-evidence/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..6f18494d1e024f91ed0e00e34c157b7ecf305ac9 --- /dev/null +++ b/skills/compliance-evidence/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Compliance Evidence" +short_description: "Work on compliance evidence for MLOps." +default_prompt: "Use this skill to help with compliance evidence in MLOps." diff --git a/skills/confidence-display/SKILL.md b/skills/confidence-display/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..663fc01535ff57b3064ac6f683fb711e53a884b9 --- /dev/null +++ b/skills/confidence-display/SKILL.md @@ -0,0 +1,29 @@ +--- +name: confidence-display +description: "Guidance for confidence display in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving confidence display, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# Confidence Display + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for confidence display. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on confidence display. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/confidence-display/agents/openai.yaml b/skills/confidence-display/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..0f007117dff267484ea5227cdab38e43c18901c8 --- /dev/null +++ b/skills/confidence-display/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Confidence Display" +short_description: "Work on confidence display for AI Product And UX." +default_prompt: "Use this skill to help with confidence display in AI Product And UX." diff --git a/skills/container-registries/SKILL.md b/skills/container-registries/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..38c48537326e6e34e6b62c0d151cb71d0993267a --- /dev/null +++ b/skills/container-registries/SKILL.md @@ -0,0 +1,29 @@ +--- +name: container-registries +description: "Guidance for container registries in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving container registries, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# Container Registries + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for container registries. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on container registries. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/container-registries/agents/openai.yaml b/skills/container-registries/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..fbd5bf171a2aa2321a63ee449a5c84a438f4f86a --- /dev/null +++ b/skills/container-registries/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Container Registries" +short_description: "Work on container registries for Cloud And DevOps." +default_prompt: "Use this skill to help with container registries in Cloud And DevOps." diff --git a/skills/context-compression/SKILL.md b/skills/context-compression/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..d41a4a71e174dbd972a33457194c397fb47ff072 --- /dev/null +++ b/skills/context-compression/SKILL.md @@ -0,0 +1,29 @@ +--- +name: context-compression +description: "Guidance for context compression in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving context compression, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Context Compression + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for context compression. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on context compression. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/context-compression/agents/openai.yaml b/skills/context-compression/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9fde0c70e24c293043b85a5dc41ba731ac3f90d8 --- /dev/null +++ b/skills/context-compression/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Context Compression" +short_description: "Work on context compression for LLM Engineering." +default_prompt: "Use this skill to help with context compression in LLM Engineering." diff --git a/skills/contrastive-learning/SKILL.md b/skills/contrastive-learning/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..9b67548a2ed07b1d9e900a62d1dc5601958ef7a9 --- /dev/null +++ b/skills/contrastive-learning/SKILL.md @@ -0,0 +1,29 @@ +--- +name: contrastive-learning +description: "Guidance for contrastive learning in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving contrastive learning, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Contrastive Learning + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for contrastive learning. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on contrastive learning. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/contrastive-learning/agents/openai.yaml b/skills/contrastive-learning/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d55e25131a8bbd068ad6a773d82301c81e250e59 --- /dev/null +++ b/skills/contrastive-learning/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Contrastive Learning" +short_description: "Work on contrastive learning for Deep Learning." +default_prompt: "Use this skill to help with contrastive learning in Deep Learning." diff --git a/skills/control-systems/SKILL.md b/skills/control-systems/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a67b79818a15599a57fa18ef2f2f13cc0a37b5e6 --- /dev/null +++ b/skills/control-systems/SKILL.md @@ -0,0 +1,29 @@ +--- +name: control-systems +description: "Guidance for control systems in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving control systems, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# Control Systems + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for control systems. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on control systems. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/control-systems/agents/openai.yaml b/skills/control-systems/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..a5d8a13b1e6118ae332387131c96b2a815c62eb4 --- /dev/null +++ b/skills/control-systems/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Control Systems" +short_description: "Work on control systems for Robotics And IoT." +default_prompt: "Use this skill to help with control systems in Robotics And IoT." diff --git a/skills/conversation-memory-design/SKILL.md b/skills/conversation-memory-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..ddb609e558b35375f5e0f3cd8316957252ecb0cb --- /dev/null +++ b/skills/conversation-memory-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: conversation-memory-design +description: "Guidance for conversation memory design in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving conversation memory design, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Conversation Memory Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for conversation memory design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on conversation memory design. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/conversation-memory-design/agents/openai.yaml b/skills/conversation-memory-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e462180571f961734164912bc6dda728ed74c2b7 --- /dev/null +++ b/skills/conversation-memory-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Conversation Memory Design" +short_description: "Work on conversation memory design for LLM Engineering." +default_prompt: "Use this skill to help with conversation memory design in LLM Engineering." diff --git a/skills/coreference-resolution/SKILL.md b/skills/coreference-resolution/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..2faae46522fd435acafe57eca461cb6597521309 --- /dev/null +++ b/skills/coreference-resolution/SKILL.md @@ -0,0 +1,29 @@ +--- +name: coreference-resolution +description: "Guidance for coreference resolution in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving coreference resolution, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Coreference Resolution + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for coreference resolution. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on coreference resolution. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/coreference-resolution/agents/openai.yaml b/skills/coreference-resolution/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..cfe114eeff95a8345c5bd09e5a0d2dd7db16b001 --- /dev/null +++ b/skills/coreference-resolution/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Coreference Resolution" +short_description: "Work on coreference resolution for Natural Language Processing." +default_prompt: "Use this skill to help with coreference resolution in Natural Language Processing." diff --git a/skills/cost-aware-inference/SKILL.md b/skills/cost-aware-inference/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..d46ff9863b1fb8b00376872e6becbd4b86377fe5 --- /dev/null +++ b/skills/cost-aware-inference/SKILL.md @@ -0,0 +1,29 @@ +--- +name: cost-aware-inference +description: "Guidance for cost aware inference in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving cost aware inference, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Cost Aware Inference + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for cost aware inference. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on cost aware inference. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/cost-aware-inference/agents/openai.yaml b/skills/cost-aware-inference/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e1c8d689896d7034f49c0d03edb36f54482f2fb4 --- /dev/null +++ b/skills/cost-aware-inference/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Cost Aware Inference" +short_description: "Work on cost aware inference for LLM Engineering." +default_prompt: "Use this skill to help with cost aware inference in LLM Engineering." diff --git a/skills/cost-optimized-queries/SKILL.md b/skills/cost-optimized-queries/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..68a8d2f8136411b6f547dcfd536c7df0189758f8 --- /dev/null +++ b/skills/cost-optimized-queries/SKILL.md @@ -0,0 +1,29 @@ +--- +name: cost-optimized-queries +description: "Guidance for cost optimized queries in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving cost optimized queries, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Cost Optimized Queries + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for cost optimized queries. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on cost optimized queries. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/cost-optimized-queries/agents/openai.yaml b/skills/cost-optimized-queries/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9ce6d83dcd41313fa8aa603224b0bc9f634466ed --- /dev/null +++ b/skills/cost-optimized-queries/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Cost Optimized Queries" +short_description: "Work on cost optimized queries for Data Engineering." +default_prompt: "Use this skill to help with cost optimized queries in Data Engineering." diff --git a/skills/crash-reporting/SKILL.md b/skills/crash-reporting/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..df631a4b34079b1f67ac8ead1c5c928887b96af0 --- /dev/null +++ b/skills/crash-reporting/SKILL.md @@ -0,0 +1,29 @@ +--- +name: crash-reporting +description: "Guidance for crash reporting in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving crash reporting, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Crash Reporting + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for crash reporting. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on crash reporting. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/crash-reporting/agents/openai.yaml b/skills/crash-reporting/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..f791f8c77b2de8fa431670c514a7ae0f2aedc332 --- /dev/null +++ b/skills/crash-reporting/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Crash Reporting" +short_description: "Work on crash reporting for Mobile App Engineering." +default_prompt: "Use this skill to help with crash reporting in Mobile App Engineering." diff --git a/skills/creative-generation-ux/SKILL.md b/skills/creative-generation-ux/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..3d7191ce3a3fb8f7f2de8559552d9b034222651c --- /dev/null +++ b/skills/creative-generation-ux/SKILL.md @@ -0,0 +1,29 @@ +--- +name: creative-generation-ux +description: "Guidance for creative generation UX in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving creative generation UX, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# Creative Generation UX + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for creative generation UX. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on creative generation UX. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/creative-generation-ux/agents/openai.yaml b/skills/creative-generation-ux/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..6cc1864df439079c96e75c5dd26e758f3dc60e75 --- /dev/null +++ b/skills/creative-generation-ux/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Creative Generation UX" +short_description: "Work on creative generation UX for AI Product And UX." +default_prompt: "Use this skill to help with creative generation UX in AI Product And UX." diff --git a/skills/cross-modal-retrieval/SKILL.md b/skills/cross-modal-retrieval/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..e171a4935249e8eba1028132da8492559627a763 --- /dev/null +++ b/skills/cross-modal-retrieval/SKILL.md @@ -0,0 +1,29 @@ +--- +name: cross-modal-retrieval +description: "Guidance for cross modal retrieval in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving cross modal retrieval, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Cross Modal Retrieval + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for cross modal retrieval. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on cross modal retrieval. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/cross-modal-retrieval/agents/openai.yaml b/skills/cross-modal-retrieval/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..cb8681cefda80bc0a320736435d1114082c8ec6a --- /dev/null +++ b/skills/cross-modal-retrieval/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Cross Modal Retrieval" +short_description: "Work on cross modal retrieval for Multimodal AI." +default_prompt: "Use this skill to help with cross modal retrieval in Multimodal AI." diff --git a/skills/cross-platform-design-systems/SKILL.md b/skills/cross-platform-design-systems/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..8bef79cc84bbb6ff26811a170fa0a3546f051899 --- /dev/null +++ b/skills/cross-platform-design-systems/SKILL.md @@ -0,0 +1,29 @@ +--- +name: cross-platform-design-systems +description: "Guidance for cross platform design systems in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving cross platform design systems, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Cross Platform Design Systems + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for cross platform design systems. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on cross platform design systems. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/cross-platform-design-systems/agents/openai.yaml b/skills/cross-platform-design-systems/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7e1ca4a53502fd92299143076fadd635731ecd02 --- /dev/null +++ b/skills/cross-platform-design-systems/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Cross Platform Design Systems" +short_description: "Work on cross platform design systems for Mobile App Engineering." +default_prompt: "Use this skill to help with cross platform design systems in Mobile App Engineering." diff --git a/skills/cross-validation-design/SKILL.md b/skills/cross-validation-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..f7504fde7a85dcb2e761caef4b8beca2164252b8 --- /dev/null +++ b/skills/cross-validation-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: cross-validation-design +description: "Guidance for cross validation design in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving cross validation design, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Cross Validation Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for cross validation design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on cross validation design. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/cross-validation-design/agents/openai.yaml b/skills/cross-validation-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..df0513ac8b77f3551d2075f25cc2bfd0f52a5927 --- /dev/null +++ b/skills/cross-validation-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Cross Validation Design" +short_description: "Work on cross validation design for Machine Learning." +default_prompt: "Use this skill to help with cross validation design in Machine Learning." diff --git a/skills/csrf-prevention/SKILL.md b/skills/csrf-prevention/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..76d3b641d6b01a3afde10a7d94f1553a21a6d357 --- /dev/null +++ b/skills/csrf-prevention/SKILL.md @@ -0,0 +1,29 @@ +--- +name: csrf-prevention +description: "Guidance for CSRF prevention in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving CSRF prevention, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# CSRF Prevention + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for CSRF prevention. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on CSRF prevention. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/csrf-prevention/agents/openai.yaml b/skills/csrf-prevention/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..2300d576781dbab596a9a7b3dfc4b89081bb3933 --- /dev/null +++ b/skills/csrf-prevention/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "CSRF Prevention" +short_description: "Work on CSRF prevention for Security And Privacy." +default_prompt: "Use this skill to help with CSRF prevention in Security And Privacy." diff --git a/skills/customer-service-ai/SKILL.md b/skills/customer-service-ai/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..41873abfd2a5345f9505774b4f8d4428a5d079c3 --- /dev/null +++ b/skills/customer-service-ai/SKILL.md @@ -0,0 +1,29 @@ +--- +name: customer-service-ai +description: "Guidance for customer service AI in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving customer service AI, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Customer Service AI + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for customer service AI. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on customer service AI. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/customer-service-ai/agents/openai.yaml b/skills/customer-service-ai/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ea3c58a3870c6f4b2c6cced0377cf72e98dba9ec --- /dev/null +++ b/skills/customer-service-ai/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Customer Service AI" +short_description: "Work on customer service AI for Domain AI." +default_prompt: "Use this skill to help with customer service AI in Domain AI." diff --git a/skills/customer-support-agents/SKILL.md b/skills/customer-support-agents/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..165722e3c52548ea7c16e153721c76ee8b1edba3 --- /dev/null +++ b/skills/customer-support-agents/SKILL.md @@ -0,0 +1,29 @@ +--- +name: customer-support-agents +description: "Guidance for customer support agents in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving customer support agents, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Customer Support Agents + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for customer support agents. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on customer support agents. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/customer-support-agents/agents/openai.yaml b/skills/customer-support-agents/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e27d38918ec91ddb475099bbd6a7236dd9670391 --- /dev/null +++ b/skills/customer-support-agents/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Customer Support Agents" +short_description: "Work on customer support agents for Agentic AI." +default_prompt: "Use this skill to help with customer support agents in Agentic AI." diff --git a/skills/customer-support-ai-ux/SKILL.md b/skills/customer-support-ai-ux/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..7b992e0628ba656affc0029dff65dd3ce69acc17 --- /dev/null +++ b/skills/customer-support-ai-ux/SKILL.md @@ -0,0 +1,29 @@ +--- +name: customer-support-ai-ux +description: "Guidance for customer support AI UX in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving customer support AI UX, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# Customer Support AI UX + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for customer support AI UX. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on customer support AI UX. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/customer-support-ai-ux/agents/openai.yaml b/skills/customer-support-ai-ux/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..fb43ea7ab8e70e1b95cd6ea629c8649781819f3d --- /dev/null +++ b/skills/customer-support-ai-ux/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Customer Support AI UX" +short_description: "Work on customer support AI UX for AI Product And UX." +default_prompt: "Use this skill to help with customer support AI UX in AI Product And UX." diff --git a/skills/cybersecurity-ai-workflows/SKILL.md b/skills/cybersecurity-ai-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..f2d572d36786bed63944c4448b49fb958c6c43a6 --- /dev/null +++ b/skills/cybersecurity-ai-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: cybersecurity-ai-workflows +description: "Guidance for cybersecurity AI workflows in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving cybersecurity AI workflows, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Cybersecurity AI Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for cybersecurity AI workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on cybersecurity AI workflows. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/cybersecurity-ai-workflows/agents/openai.yaml b/skills/cybersecurity-ai-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..2538fe6b239d5b78b072a18f16d2ac23a7059658 --- /dev/null +++ b/skills/cybersecurity-ai-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Cybersecurity AI Workflows" +short_description: "Work on cybersecurity AI workflows for Domain AI." +default_prompt: "Use this skill to help with cybersecurity AI workflows in Domain AI." diff --git a/skills/dashboard-metric-definitions/SKILL.md b/skills/dashboard-metric-definitions/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..6701d8ecdbfdc15f9dd180784c6d00abbd3e1f14 --- /dev/null +++ b/skills/dashboard-metric-definitions/SKILL.md @@ -0,0 +1,29 @@ +--- +name: dashboard-metric-definitions +description: "Guidance for dashboard metric definitions in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving dashboard metric definitions, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# Dashboard Metric Definitions + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for dashboard metric definitions. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on dashboard metric definitions. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/dashboard-metric-definitions/agents/openai.yaml b/skills/dashboard-metric-definitions/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..4927a266e349766c99488a0320ba69ab3716a8ad --- /dev/null +++ b/skills/dashboard-metric-definitions/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Dashboard Metric Definitions" +short_description: "Work on dashboard metric definitions for Databases And Analytics." +default_prompt: "Use this skill to help with dashboard metric definitions in Databases And Analytics." diff --git a/skills/data-analysis-agents/SKILL.md b/skills/data-analysis-agents/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..e516dbf7384fa11228fd6e96ea76f5908c354330 --- /dev/null +++ b/skills/data-analysis-agents/SKILL.md @@ -0,0 +1,29 @@ +--- +name: data-analysis-agents +description: "Guidance for data analysis agents in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving data analysis agents, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Data Analysis Agents + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for data analysis agents. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on data analysis agents. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/data-analysis-agents/agents/openai.yaml b/skills/data-analysis-agents/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7e343b0285b63ac453a29a5968a1cfcd4a7f477f --- /dev/null +++ b/skills/data-analysis-agents/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Data Analysis Agents" +short_description: "Work on data analysis agents for Agentic AI." +default_prompt: "Use this skill to help with data analysis agents in Agentic AI." diff --git a/skills/data-backfills/SKILL.md b/skills/data-backfills/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..ce4ec0578e9f67a8f1cf7df38811b2a5527855b7 --- /dev/null +++ b/skills/data-backfills/SKILL.md @@ -0,0 +1,29 @@ +--- +name: data-backfills +description: "Guidance for data backfills in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving data backfills, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Data Backfills + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for data backfills. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on data backfills. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/data-backfills/agents/openai.yaml b/skills/data-backfills/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3463f20b9951ab6da559f43f1290d3d0743abdcf --- /dev/null +++ b/skills/data-backfills/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Data Backfills" +short_description: "Work on data backfills for Data Engineering." +default_prompt: "Use this skill to help with data backfills in Data Engineering." diff --git a/skills/data-cataloging/SKILL.md b/skills/data-cataloging/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..2fc58979a03e45f6ceb2503e5620bf17d92cc4f8 --- /dev/null +++ b/skills/data-cataloging/SKILL.md @@ -0,0 +1,29 @@ +--- +name: data-cataloging +description: "Guidance for data cataloging in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving data cataloging, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Data Cataloging + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for data cataloging. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on data cataloging. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/data-cataloging/agents/openai.yaml b/skills/data-cataloging/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9835d380275a48aac9a9ebf3984752c8d45ab647 --- /dev/null +++ b/skills/data-cataloging/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Data Cataloging" +short_description: "Work on data cataloging for Data Engineering." +default_prompt: "Use this skill to help with data cataloging in Data Engineering." diff --git a/skills/data-contracts/SKILL.md b/skills/data-contracts/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..e14b55798a352fd230ff4399a2049d0a7e5e2b20 --- /dev/null +++ b/skills/data-contracts/SKILL.md @@ -0,0 +1,29 @@ +--- +name: data-contracts +description: "Guidance for data contracts in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving data contracts, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Data Contracts + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for data contracts. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on data contracts. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/data-contracts/agents/openai.yaml b/skills/data-contracts/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..401da8c51e0567fde6776f6a5879f427397770b9 --- /dev/null +++ b/skills/data-contracts/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Data Contracts" +short_description: "Work on data contracts for Data Engineering." +default_prompt: "Use this skill to help with data contracts in Data Engineering." diff --git a/skills/data-encryption/SKILL.md b/skills/data-encryption/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..0b850feee61bf0fef335b60764efb6818d7a55c8 --- /dev/null +++ b/skills/data-encryption/SKILL.md @@ -0,0 +1,29 @@ +--- +name: data-encryption +description: "Guidance for data encryption in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving data encryption, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# Data Encryption + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for data encryption. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on data encryption. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/data-encryption/agents/openai.yaml b/skills/data-encryption/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7499ae1f43f533346edf99ad21662593fca9bead --- /dev/null +++ b/skills/data-encryption/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Data Encryption" +short_description: "Work on data encryption for Security And Privacy." +default_prompt: "Use this skill to help with data encryption in Security And Privacy." diff --git a/skills/data-leakage-audits/SKILL.md b/skills/data-leakage-audits/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..23de46a852be742f84e06f7252261384cf3e66cf --- /dev/null +++ b/skills/data-leakage-audits/SKILL.md @@ -0,0 +1,29 @@ +--- +name: data-leakage-audits +description: "Guidance for data leakage audits in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving data leakage audits, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Data Leakage Audits + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for data leakage audits. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on data leakage audits. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/data-leakage-audits/agents/openai.yaml b/skills/data-leakage-audits/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3773cf88aabb5e31a6b999935aa9e2ae3684d967 --- /dev/null +++ b/skills/data-leakage-audits/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Data Leakage Audits" +short_description: "Work on data leakage audits for Machine Learning." +default_prompt: "Use this skill to help with data leakage audits in Machine Learning." diff --git a/skills/data-lineage/SKILL.md b/skills/data-lineage/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..c8ae1528e9b4691b701dbcf1188ea1b9f5108e64 --- /dev/null +++ b/skills/data-lineage/SKILL.md @@ -0,0 +1,29 @@ +--- +name: data-lineage +description: "Guidance for data lineage in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving data lineage, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Data Lineage + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for data lineage. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on data lineage. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/data-lineage/agents/openai.yaml b/skills/data-lineage/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9ef724fe424a01c1e1b60bf1144917d4091c473c --- /dev/null +++ b/skills/data-lineage/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Data Lineage" +short_description: "Work on data lineage for Data Engineering." +default_prompt: "Use this skill to help with data lineage in Data Engineering." diff --git a/skills/data-quality-checks/SKILL.md b/skills/data-quality-checks/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..43dba5de28395016322f9d5512ed915b25497906 --- /dev/null +++ b/skills/data-quality-checks/SKILL.md @@ -0,0 +1,29 @@ +--- +name: data-quality-checks +description: "Guidance for data quality checks in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving data quality checks, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Data Quality Checks + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for data quality checks. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on data quality checks. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/data-quality-checks/agents/openai.yaml b/skills/data-quality-checks/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..02682163a111af12444f869ee90c133eb340071c --- /dev/null +++ b/skills/data-quality-checks/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Data Quality Checks" +short_description: "Work on data quality checks for Data Engineering." +default_prompt: "Use this skill to help with data quality checks in Data Engineering." diff --git a/skills/data-visualization-ui/SKILL.md b/skills/data-visualization-ui/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..70fded2a35ae79714bdfbac0424fc03ffec66c24 --- /dev/null +++ b/skills/data-visualization-ui/SKILL.md @@ -0,0 +1,29 @@ +--- +name: data-visualization-ui +description: "Guidance for data visualization UI in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving data visualization UI, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Data Visualization UI + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for data visualization UI. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on data visualization UI. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/data-visualization-ui/agents/openai.yaml b/skills/data-visualization-ui/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..a96bcbf4090a794032fac20116b42e3773d4044b --- /dev/null +++ b/skills/data-visualization-ui/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Data Visualization UI" +short_description: "Work on data visualization UI for Web Engineering." +default_prompt: "Use this skill to help with data visualization UI in Web Engineering." diff --git a/skills/data-warehouse-sql/SKILL.md b/skills/data-warehouse-sql/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..6f1d51c322cacfcd638e624ca36fb119227d924d --- /dev/null +++ b/skills/data-warehouse-sql/SKILL.md @@ -0,0 +1,29 @@ +--- +name: data-warehouse-sql +description: "Guidance for data warehouse SQL in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving data warehouse SQL, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# Data Warehouse SQL + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for data warehouse SQL. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on data warehouse SQL. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/data-warehouse-sql/agents/openai.yaml b/skills/data-warehouse-sql/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..988fb8e6d9201cc3b82ffcd04c3cf15b203175d1 --- /dev/null +++ b/skills/data-warehouse-sql/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Data Warehouse SQL" +short_description: "Work on data warehouse SQL for Databases And Analytics." +default_prompt: "Use this skill to help with data warehouse SQL in Databases And Analytics." diff --git a/skills/database-migrations/SKILL.md b/skills/database-migrations/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..49d1581637db016f5e0104785519885068649f47 --- /dev/null +++ b/skills/database-migrations/SKILL.md @@ -0,0 +1,29 @@ +--- +name: database-migrations +description: "Guidance for database migrations in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving database migrations, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# Database Migrations + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for database migrations. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on database migrations. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/database-migrations/agents/openai.yaml b/skills/database-migrations/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..fd79b12bb9e0921fd04de974fc6de03c5d0adf10 --- /dev/null +++ b/skills/database-migrations/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Database Migrations" +short_description: "Work on database migrations for Cloud And DevOps." +default_prompt: "Use this skill to help with database migrations in Cloud And DevOps." diff --git a/skills/dataset-documentation/SKILL.md b/skills/dataset-documentation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..c60b2b9816baaa8d152ff7616a36aa85cdc4c0fc --- /dev/null +++ b/skills/dataset-documentation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: dataset-documentation +description: "Guidance for dataset documentation in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving dataset documentation, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Dataset Documentation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for dataset documentation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on dataset documentation. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/dataset-documentation/agents/openai.yaml b/skills/dataset-documentation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..0b9cbd52da5e11560deb2656453b2ee4fb34bb60 --- /dev/null +++ b/skills/dataset-documentation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Dataset Documentation" +short_description: "Work on dataset documentation for Research And Scientific AI." +default_prompt: "Use this skill to help with dataset documentation in Research And Scientific AI." diff --git a/skills/dataset-pair-generation/SKILL.md b/skills/dataset-pair-generation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..e7fdb3e3dd291dd64ade726c8f1e6882f180739c --- /dev/null +++ b/skills/dataset-pair-generation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: dataset-pair-generation +description: "Guidance for dataset pair generation in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving dataset pair generation, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Dataset Pair Generation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for dataset pair generation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on dataset pair generation. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/dataset-pair-generation/agents/openai.yaml b/skills/dataset-pair-generation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..de4ede0718f066c3b237919ea6b565377b6cebd3 --- /dev/null +++ b/skills/dataset-pair-generation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Dataset Pair Generation" +short_description: "Work on dataset pair generation for Multimodal AI." +default_prompt: "Use this skill to help with dataset pair generation in Multimodal AI." diff --git a/skills/dataset-versioning/SKILL.md b/skills/dataset-versioning/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..1b6d1fd1af7f32d59c75f8cac2a68e9eb8cdd263 --- /dev/null +++ b/skills/dataset-versioning/SKILL.md @@ -0,0 +1,29 @@ +--- +name: dataset-versioning +description: "Guidance for dataset versioning in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving dataset versioning, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# Dataset Versioning + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for dataset versioning. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on dataset versioning. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/dataset-versioning/agents/openai.yaml b/skills/dataset-versioning/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..bdf45eb79547376e38d95e179584e9fbd98c7ce8 --- /dev/null +++ b/skills/dataset-versioning/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Dataset Versioning" +short_description: "Work on dataset versioning for MLOps." +default_prompt: "Use this skill to help with dataset versioning in MLOps." diff --git a/skills/dbt-model-design/SKILL.md b/skills/dbt-model-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..8621a9fc84b8b91076c730748a7a5b6a6fc22e25 --- /dev/null +++ b/skills/dbt-model-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: dbt-model-design +description: "Guidance for dbt model design in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving dbt model design, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# DBT Model Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for dbt model design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on dbt model design. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/dbt-model-design/agents/openai.yaml b/skills/dbt-model-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..c9d0beb6d8b513bb0048923826f3e36a07e663e1 --- /dev/null +++ b/skills/dbt-model-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "DBT Model Design" +short_description: "Work on dbt model design for Databases And Analytics." +default_prompt: "Use this skill to help with dbt model design in Databases And Analytics." diff --git a/skills/deep-linking/SKILL.md b/skills/deep-linking/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..fde2ca95dfb8695ba948a20f36a7bd419dd4e743 --- /dev/null +++ b/skills/deep-linking/SKILL.md @@ -0,0 +1,29 @@ +--- +name: deep-linking +description: "Guidance for deep linking in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving deep linking, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Deep Linking + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for deep linking. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on deep linking. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/deep-linking/agents/openai.yaml b/skills/deep-linking/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..fcdd86a4b199c864c5ab3f3c3c2b2d60ef071bf7 --- /dev/null +++ b/skills/deep-linking/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Deep Linking" +short_description: "Work on deep linking for Mobile App Engineering." +default_prompt: "Use this skill to help with deep linking in Mobile App Engineering." diff --git a/skills/dependency-vulnerability-handling/SKILL.md b/skills/dependency-vulnerability-handling/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..29a104caefc9ef32283a9215779b4372c2c50ea8 --- /dev/null +++ b/skills/dependency-vulnerability-handling/SKILL.md @@ -0,0 +1,29 @@ +--- +name: dependency-vulnerability-handling +description: "Guidance for dependency vulnerability handling in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving dependency vulnerability handling, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# Dependency Vulnerability Handling + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for dependency vulnerability handling. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on dependency vulnerability handling. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/dependency-vulnerability-handling/agents/openai.yaml b/skills/dependency-vulnerability-handling/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..6d38ef3a0c3ce9879823fad3e8c57ea6c9ae8e52 --- /dev/null +++ b/skills/dependency-vulnerability-handling/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Dependency Vulnerability Handling" +short_description: "Work on dependency vulnerability handling for Security And Privacy." +default_prompt: "Use this skill to help with dependency vulnerability handling in Security And Privacy." diff --git a/skills/depth-estimation/SKILL.md b/skills/depth-estimation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..e3cc0b9990157ae89bf13ab2389ffd269977cd1a --- /dev/null +++ b/skills/depth-estimation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: depth-estimation +description: "Guidance for depth estimation in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving depth estimation, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Depth Estimation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for depth estimation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on depth estimation. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/depth-estimation/agents/openai.yaml b/skills/depth-estimation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..f344e04bf3aa13f363231f05c87fd07543dda8fc --- /dev/null +++ b/skills/depth-estimation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Depth Estimation" +short_description: "Work on depth estimation for Computer Vision." +default_prompt: "Use this skill to help with depth estimation in Computer Vision." diff --git a/skills/design-system-components/SKILL.md b/skills/design-system-components/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..418e8a42f6bef8cd2bb0b565eff6ed3b1620f19c --- /dev/null +++ b/skills/design-system-components/SKILL.md @@ -0,0 +1,29 @@ +--- +name: design-system-components +description: "Guidance for design system components in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving design system components, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Design System Components + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for design system components. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on design system components. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/design-system-components/agents/openai.yaml b/skills/design-system-components/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..5561f384f534766f4f1485d708fdf90f63068151 --- /dev/null +++ b/skills/design-system-components/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Design System Components" +short_description: "Work on design system components for Web Engineering." +default_prompt: "Use this skill to help with design system components in Web Engineering." diff --git a/skills/device-permissions/SKILL.md b/skills/device-permissions/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..635eaac274767142b93ae2537906e99a6986919e --- /dev/null +++ b/skills/device-permissions/SKILL.md @@ -0,0 +1,29 @@ +--- +name: device-permissions +description: "Guidance for device permissions in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving device permissions, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Device Permissions + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for device permissions. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on device permissions. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/device-permissions/agents/openai.yaml b/skills/device-permissions/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..025ba77d517abb9f929440d8c127bc0bb420f72a --- /dev/null +++ b/skills/device-permissions/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Device Permissions" +short_description: "Work on device permissions for Mobile App Engineering." +default_prompt: "Use this skill to help with device permissions in Mobile App Engineering." diff --git a/skills/device-provisioning/SKILL.md b/skills/device-provisioning/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..c15a810c1b69f8fb59601615747e70eae7921ced --- /dev/null +++ b/skills/device-provisioning/SKILL.md @@ -0,0 +1,29 @@ +--- +name: device-provisioning +description: "Guidance for device provisioning in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving device provisioning, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# Device Provisioning + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for device provisioning. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on device provisioning. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/device-provisioning/agents/openai.yaml b/skills/device-provisioning/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..be6677a591ea30efb24dc654537f8afadc58a627 --- /dev/null +++ b/skills/device-provisioning/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Device Provisioning" +short_description: "Work on device provisioning for Robotics And IoT." +default_prompt: "Use this skill to help with device provisioning in Robotics And IoT." diff --git a/skills/diffusion-model-training/SKILL.md b/skills/diffusion-model-training/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..5663f662e1df72cc194b5b21eebdc801fb07aa37 --- /dev/null +++ b/skills/diffusion-model-training/SKILL.md @@ -0,0 +1,29 @@ +--- +name: diffusion-model-training +description: "Guidance for diffusion model training in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving diffusion model training, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Diffusion Model Training + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for diffusion model training. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on diffusion model training. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/diffusion-model-training/agents/openai.yaml b/skills/diffusion-model-training/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..39d9df1e36f1008767b94ec7fe35f2056bd14556 --- /dev/null +++ b/skills/diffusion-model-training/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Diffusion Model Training" +short_description: "Work on diffusion model training for Deep Learning." +default_prompt: "Use this skill to help with diffusion model training in Deep Learning." diff --git a/skills/digital-twins/SKILL.md b/skills/digital-twins/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..165b5e365e2677a3e0a781315bb7edba255ef4b5 --- /dev/null +++ b/skills/digital-twins/SKILL.md @@ -0,0 +1,29 @@ +--- +name: digital-twins +description: "Guidance for digital twins in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving digital twins, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# Digital Twins + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for digital twins. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on digital twins. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/digital-twins/agents/openai.yaml b/skills/digital-twins/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..4a9e5cf28df3796c4292e9bdf86e9dd80959a175 --- /dev/null +++ b/skills/digital-twins/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Digital Twins" +short_description: "Work on digital twins for Robotics And IoT." +default_prompt: "Use this skill to help with digital twins in Robotics And IoT." diff --git a/skills/dimensionality-reduction/SKILL.md b/skills/dimensionality-reduction/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..ba9a196e4c69cf2abb96726c7e21e6c3bddc2043 --- /dev/null +++ b/skills/dimensionality-reduction/SKILL.md @@ -0,0 +1,29 @@ +--- +name: dimensionality-reduction +description: "Guidance for dimensionality reduction in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving dimensionality reduction, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Dimensionality Reduction + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for dimensionality reduction. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on dimensionality reduction. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/dimensionality-reduction/agents/openai.yaml b/skills/dimensionality-reduction/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..0d6324c0e6b3aea159d7c2dff2aaeb51763c5110 --- /dev/null +++ b/skills/dimensionality-reduction/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Dimensionality Reduction" +short_description: "Work on dimensionality reduction for Machine Learning." +default_prompt: "Use this skill to help with dimensionality reduction in Machine Learning." diff --git a/skills/disaster-recovery/SKILL.md b/skills/disaster-recovery/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..057fcd3dbc4002adc7057c3ba97068b77ce4a52d --- /dev/null +++ b/skills/disaster-recovery/SKILL.md @@ -0,0 +1,29 @@ +--- +name: disaster-recovery +description: "Guidance for disaster recovery in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving disaster recovery, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# Disaster Recovery + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for disaster recovery. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on disaster recovery. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/disaster-recovery/agents/openai.yaml b/skills/disaster-recovery/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7a35db777fe1ee747f42dc744bbb8b5ff4257c03 --- /dev/null +++ b/skills/disaster-recovery/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Disaster Recovery" +short_description: "Work on disaster recovery for Cloud And DevOps." +default_prompt: "Use this skill to help with disaster recovery in Cloud And DevOps." diff --git a/skills/distributed-training/SKILL.md b/skills/distributed-training/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..33e03772175e084b9f7013e9ec19be8ac03da251 --- /dev/null +++ b/skills/distributed-training/SKILL.md @@ -0,0 +1,29 @@ +--- +name: distributed-training +description: "Guidance for distributed training in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving distributed training, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Distributed Training + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for distributed training. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on distributed training. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/distributed-training/agents/openai.yaml b/skills/distributed-training/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..225c04b4699d9a269b49a484b500e4fcaad34f40 --- /dev/null +++ b/skills/distributed-training/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Distributed Training" +short_description: "Work on distributed training for Deep Learning." +default_prompt: "Use this skill to help with distributed training in Deep Learning." diff --git a/skills/docker-packaging/SKILL.md b/skills/docker-packaging/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..d05c220b325f930908de8cb98b1f4967f92445fb --- /dev/null +++ b/skills/docker-packaging/SKILL.md @@ -0,0 +1,29 @@ +--- +name: docker-packaging +description: "Guidance for Docker packaging in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving Docker packaging, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# Docker Packaging + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for Docker packaging. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on Docker packaging. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/docker-packaging/agents/openai.yaml b/skills/docker-packaging/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..bde2ac8a420875b498146c607e7903aa626f1139 --- /dev/null +++ b/skills/docker-packaging/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Docker Packaging" +short_description: "Work on Docker packaging for Cloud And DevOps." +default_prompt: "Use this skill to help with Docker packaging in Cloud And DevOps." diff --git a/skills/document-layout-analysis/SKILL.md b/skills/document-layout-analysis/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..dabaf39bf95538fdc1795e74b37d3de6e717457b --- /dev/null +++ b/skills/document-layout-analysis/SKILL.md @@ -0,0 +1,29 @@ +--- +name: document-layout-analysis +description: "Guidance for document layout analysis in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving document layout analysis, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Document Layout Analysis + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for document layout analysis. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on document layout analysis. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/document-layout-analysis/agents/openai.yaml b/skills/document-layout-analysis/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..adcdaa5bcc51d15aff726fc8fb40d19b68a28f7f --- /dev/null +++ b/skills/document-layout-analysis/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Document Layout Analysis" +short_description: "Work on document layout analysis for Computer Vision." +default_prompt: "Use this skill to help with document layout analysis in Computer Vision." diff --git a/skills/document-parsing/SKILL.md b/skills/document-parsing/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..321261c32b162e4e71bea195adc82d4e1fcd0c7a --- /dev/null +++ b/skills/document-parsing/SKILL.md @@ -0,0 +1,29 @@ +--- +name: document-parsing +description: "Guidance for document parsing in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving document parsing, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Document Parsing + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for document parsing. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on document parsing. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/document-parsing/agents/openai.yaml b/skills/document-parsing/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d7421e3acb1e0b047cf0d625205d40af2eefa181 --- /dev/null +++ b/skills/document-parsing/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Document Parsing" +short_description: "Work on document parsing for Natural Language Processing." +default_prompt: "Use this skill to help with document parsing in Natural Language Processing." diff --git a/skills/document-vqa/SKILL.md b/skills/document-vqa/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..9f3f97138b9143acca032b4b8604eea00cde5a92 --- /dev/null +++ b/skills/document-vqa/SKILL.md @@ -0,0 +1,29 @@ +--- +name: document-vqa +description: "Guidance for document VQA in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving document VQA, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Document VQA + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for document VQA. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on document VQA. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/document-vqa/agents/openai.yaml b/skills/document-vqa/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..f3559be642439acc0cf6ad52482f906f392d2e88 --- /dev/null +++ b/skills/document-vqa/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Document VQA" +short_description: "Work on document VQA for Multimodal AI." +default_prompt: "Use this skill to help with document VQA in Multimodal AI." diff --git a/skills/drift-detection/SKILL.md b/skills/drift-detection/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..7f96fe9c48965a253b4260bfe47f4ddd04582f83 --- /dev/null +++ b/skills/drift-detection/SKILL.md @@ -0,0 +1,29 @@ +--- +name: drift-detection +description: "Guidance for drift detection in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving drift detection, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# Drift Detection + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for drift detection. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on drift detection. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/drift-detection/agents/openai.yaml b/skills/drift-detection/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..585b27600e72293d24aec333d14381d40d587b54 --- /dev/null +++ b/skills/drift-detection/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Drift Detection" +short_description: "Work on drift detection for MLOps." +default_prompt: "Use this skill to help with drift detection in MLOps." diff --git a/skills/edge-inference-devices/SKILL.md b/skills/edge-inference-devices/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..93cedfbc628bf92ed5ebb045475e839d979e91f7 --- /dev/null +++ b/skills/edge-inference-devices/SKILL.md @@ -0,0 +1,29 @@ +--- +name: edge-inference-devices +description: "Guidance for edge inference devices in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving edge inference devices, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# Edge Inference Devices + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for edge inference devices. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on edge inference devices. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/edge-inference-devices/agents/openai.yaml b/skills/edge-inference-devices/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..faea2933b488d0d5ce494103a37c797bafb2322b --- /dev/null +++ b/skills/edge-inference-devices/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Edge Inference Devices" +short_description: "Work on edge inference devices for Robotics And IoT." +default_prompt: "Use this skill to help with edge inference devices in Robotics And IoT." diff --git a/skills/edge-ml-deployment/SKILL.md b/skills/edge-ml-deployment/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..33113172359ee8962a0f511240145a82563e750d --- /dev/null +++ b/skills/edge-ml-deployment/SKILL.md @@ -0,0 +1,29 @@ +--- +name: edge-ml-deployment +description: "Guidance for edge ML deployment in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving edge ML deployment, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# Edge ML Deployment + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for edge ML deployment. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on edge ML deployment. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/edge-ml-deployment/agents/openai.yaml b/skills/edge-ml-deployment/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9f13bbccd712fb36ee4886c6395cd7df2c6c0d24 --- /dev/null +++ b/skills/edge-ml-deployment/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Edge ML Deployment" +short_description: "Work on edge ML deployment for MLOps." +default_prompt: "Use this skill to help with edge ML deployment in MLOps." diff --git a/skills/edge-vision-deployment/SKILL.md b/skills/edge-vision-deployment/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a3fcdfb9ea6362a7fcab69e59ef1ffbf789fe799 --- /dev/null +++ b/skills/edge-vision-deployment/SKILL.md @@ -0,0 +1,29 @@ +--- +name: edge-vision-deployment +description: "Guidance for edge vision deployment in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving edge vision deployment, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Edge Vision Deployment + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for edge vision deployment. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on edge vision deployment. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/edge-vision-deployment/agents/openai.yaml b/skills/edge-vision-deployment/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ad61a846c5b4e5b9a54af78763e6718f6dfb0f48 --- /dev/null +++ b/skills/edge-vision-deployment/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Edge Vision Deployment" +short_description: "Work on edge vision deployment for Computer Vision." +default_prompt: "Use this skill to help with edge vision deployment in Computer Vision." diff --git a/skills/education-ai-workflows/SKILL.md b/skills/education-ai-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..b4843be1db9663f139bbb8cd0bb7c2c16af4a696 --- /dev/null +++ b/skills/education-ai-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: education-ai-workflows +description: "Guidance for education AI workflows in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving education AI workflows, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Education AI Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for education AI workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on education AI workflows. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/education-ai-workflows/agents/openai.yaml b/skills/education-ai-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..8b3b54eb741efc8d7b8f06492e3554fff737f090 --- /dev/null +++ b/skills/education-ai-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Education AI Workflows" +short_description: "Work on education AI workflows for Domain AI." +default_prompt: "Use this skill to help with education AI workflows in Domain AI." diff --git a/skills/elasticsearch-search-design/SKILL.md b/skills/elasticsearch-search-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..7b6c538240676c76acb781eb5e7011ab61e855d7 --- /dev/null +++ b/skills/elasticsearch-search-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: elasticsearch-search-design +description: "Guidance for Elasticsearch search design in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving Elasticsearch search design, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# Elasticsearch Search Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for Elasticsearch search design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on Elasticsearch search design. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/elasticsearch-search-design/agents/openai.yaml b/skills/elasticsearch-search-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..8997d3e8050142c18430a7a906fae9200ae8104b --- /dev/null +++ b/skills/elasticsearch-search-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Elasticsearch Search Design" +short_description: "Work on Elasticsearch search design for Databases And Analytics." +default_prompt: "Use this skill to help with Elasticsearch search design in Databases And Analytics." diff --git a/skills/elt-pipeline-design/SKILL.md b/skills/elt-pipeline-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..f2ff06bf953167dcfa53fe90ed3fa7464d323b54 --- /dev/null +++ b/skills/elt-pipeline-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: elt-pipeline-design +description: "Guidance for ELT pipeline design in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving ELT pipeline design, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# ELT Pipeline Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for ELT pipeline design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on ELT pipeline design. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/elt-pipeline-design/agents/openai.yaml b/skills/elt-pipeline-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..c6c7dcbac3c9a551c85a0cafdf7000e62ea5e5fa --- /dev/null +++ b/skills/elt-pipeline-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "ELT Pipeline Design" +short_description: "Work on ELT pipeline design for Data Engineering." +default_prompt: "Use this skill to help with ELT pipeline design in Data Engineering." diff --git a/skills/embedded-linux/SKILL.md b/skills/embedded-linux/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..bb925ef21c0bcd85080326fd61939f369aefe587 --- /dev/null +++ b/skills/embedded-linux/SKILL.md @@ -0,0 +1,29 @@ +--- +name: embedded-linux +description: "Guidance for embedded Linux in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving embedded Linux, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# Embedded Linux + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for embedded Linux. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on embedded Linux. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/embedded-linux/agents/openai.yaml b/skills/embedded-linux/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e88862eff160ee86c8e99fb64fe9334fa34f5a8c --- /dev/null +++ b/skills/embedded-linux/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Embedded Linux" +short_description: "Work on embedded Linux for Robotics And IoT." +default_prompt: "Use this skill to help with embedded Linux in Robotics And IoT." diff --git a/skills/embedding-pipeline-design/SKILL.md b/skills/embedding-pipeline-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..8fa74180467256e11f1669aebf8960fd99dd244c --- /dev/null +++ b/skills/embedding-pipeline-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: embedding-pipeline-design +description: "Guidance for embedding pipeline design in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving embedding pipeline design, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Embedding Pipeline Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for embedding pipeline design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on embedding pipeline design. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/embedding-pipeline-design/agents/openai.yaml b/skills/embedding-pipeline-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..775b177fb40bcc275af1c0995fc473d97cb3ca65 --- /dev/null +++ b/skills/embedding-pipeline-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Embedding Pipeline Design" +short_description: "Work on embedding pipeline design for LLM Engineering." +default_prompt: "Use this skill to help with embedding pipeline design in LLM Engineering." diff --git a/skills/energy-ai-workflows/SKILL.md b/skills/energy-ai-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..103d6eb89d0305ceb285a98856446115e565b9e7 --- /dev/null +++ b/skills/energy-ai-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: energy-ai-workflows +description: "Guidance for energy AI workflows in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving energy AI workflows, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Energy AI Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for energy AI workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on energy AI workflows. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/energy-ai-workflows/agents/openai.yaml b/skills/energy-ai-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b235ff3fe9aade04d503f0de14c59b3a713b5136 --- /dev/null +++ b/skills/energy-ai-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Energy AI Workflows" +short_description: "Work on energy AI workflows for Domain AI." +default_prompt: "Use this skill to help with energy AI workflows in Domain AI." diff --git a/skills/ensemble-methods/SKILL.md b/skills/ensemble-methods/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..09ff87cd209eebf67d5a217778821a639a85c962 --- /dev/null +++ b/skills/ensemble-methods/SKILL.md @@ -0,0 +1,29 @@ +--- +name: ensemble-methods +description: "Guidance for ensemble methods in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving ensemble methods, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Ensemble Methods + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for ensemble methods. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on ensemble methods. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/ensemble-methods/agents/openai.yaml b/skills/ensemble-methods/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ca60f09a493c2285e684b09d2ddde8de0d9ebc89 --- /dev/null +++ b/skills/ensemble-methods/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Ensemble Methods" +short_description: "Work on ensemble methods for Machine Learning." +default_prompt: "Use this skill to help with ensemble methods in Machine Learning." diff --git a/skills/enterprise-permission-ux/SKILL.md b/skills/enterprise-permission-ux/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..08aa6455ff65712a900890da2c6e15bc3cab81aa --- /dev/null +++ b/skills/enterprise-permission-ux/SKILL.md @@ -0,0 +1,29 @@ +--- +name: enterprise-permission-ux +description: "Guidance for enterprise permission UX in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving enterprise permission UX, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# Enterprise Permission UX + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for enterprise permission UX. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on enterprise permission UX. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/enterprise-permission-ux/agents/openai.yaml b/skills/enterprise-permission-ux/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7d9cc27b4edab9140759c4c61cbbd2349261e1b7 --- /dev/null +++ b/skills/enterprise-permission-ux/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Enterprise Permission UX" +short_description: "Work on enterprise permission UX for AI Product And UX." +default_prompt: "Use this skill to help with enterprise permission UX in AI Product And UX." diff --git a/skills/enterprise-task-agents/SKILL.md b/skills/enterprise-task-agents/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..bc03a2598def4b82ba20989631775a162a03914b --- /dev/null +++ b/skills/enterprise-task-agents/SKILL.md @@ -0,0 +1,29 @@ +--- +name: enterprise-task-agents +description: "Guidance for enterprise task agents in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving enterprise task agents, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Enterprise Task Agents + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for enterprise task agents. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on enterprise task agents. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/enterprise-task-agents/agents/openai.yaml b/skills/enterprise-task-agents/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..959069d5b1af3ea5d6481a97118a6ab3e0dd5ba7 --- /dev/null +++ b/skills/enterprise-task-agents/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Enterprise Task Agents" +short_description: "Work on enterprise task agents for Agentic AI." +default_prompt: "Use this skill to help with enterprise task agents in Agentic AI." diff --git a/skills/entity-linking/SKILL.md b/skills/entity-linking/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..c65f16c22f14313a65c6e5e645fab25983a84791 --- /dev/null +++ b/skills/entity-linking/SKILL.md @@ -0,0 +1,29 @@ +--- +name: entity-linking +description: "Guidance for entity linking in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving entity linking, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Entity Linking + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for entity linking. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on entity linking. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/entity-linking/agents/openai.yaml b/skills/entity-linking/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..46cfd7e65869a25f96344bd0580ccf2a92191181 --- /dev/null +++ b/skills/entity-linking/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Entity Linking" +short_description: "Work on entity linking for Natural Language Processing." +default_prompt: "Use this skill to help with entity linking in Natural Language Processing." diff --git a/skills/error-recovery-flows/SKILL.md b/skills/error-recovery-flows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..f8221d8f46b8bb890d01a438c94d952f21b10a7f --- /dev/null +++ b/skills/error-recovery-flows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: error-recovery-flows +description: "Guidance for error recovery flows in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving error recovery flows, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# Error Recovery Flows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for error recovery flows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on error recovery flows. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/error-recovery-flows/agents/openai.yaml b/skills/error-recovery-flows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7ea5a1229d84b0b05a89f267ebd04326b1eef352 --- /dev/null +++ b/skills/error-recovery-flows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Error Recovery Flows" +short_description: "Work on error recovery flows for AI Product And UX." +default_prompt: "Use this skill to help with error recovery flows in AI Product And UX." diff --git a/skills/ethics-review-support/SKILL.md b/skills/ethics-review-support/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..9868121cfe092d2d3e7aa0870b9252aac7e098f3 --- /dev/null +++ b/skills/ethics-review-support/SKILL.md @@ -0,0 +1,29 @@ +--- +name: ethics-review-support +description: "Guidance for ethics review support in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving ethics review support, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Ethics Review Support + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for ethics review support. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on ethics review support. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/ethics-review-support/agents/openai.yaml b/skills/ethics-review-support/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..83c12b51046feb5868b82e24112b4c7878387e52 --- /dev/null +++ b/skills/ethics-review-support/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Ethics Review Support" +short_description: "Work on ethics review support for Research And Scientific AI." +default_prompt: "Use this skill to help with ethics review support in Research And Scientific AI." diff --git a/skills/etl-pipeline-design/SKILL.md b/skills/etl-pipeline-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..e4725927bd4366b1b43aa70ac3fcdf887b043859 --- /dev/null +++ b/skills/etl-pipeline-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: etl-pipeline-design +description: "Guidance for ETL pipeline design in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving ETL pipeline design, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# ETL Pipeline Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for ETL pipeline design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on ETL pipeline design. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/etl-pipeline-design/agents/openai.yaml b/skills/etl-pipeline-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..1099c2f24c02a083c9cac5a8db7ea22eddc56afc --- /dev/null +++ b/skills/etl-pipeline-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "ETL Pipeline Design" +short_description: "Work on ETL pipeline design for Data Engineering." +default_prompt: "Use this skill to help with ETL pipeline design in Data Engineering." diff --git a/skills/evaluation-dashboards/SKILL.md b/skills/evaluation-dashboards/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..2e1c1567e6a886d2135ef9938a17f5dbec9a4569 --- /dev/null +++ b/skills/evaluation-dashboards/SKILL.md @@ -0,0 +1,29 @@ +--- +name: evaluation-dashboards +description: "Guidance for evaluation dashboards in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving evaluation dashboards, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# Evaluation Dashboards + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for evaluation dashboards. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on evaluation dashboards. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/evaluation-dashboards/agents/openai.yaml b/skills/evaluation-dashboards/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9e2bc656b722290193b4c7d9fb0307c797e8f5ba --- /dev/null +++ b/skills/evaluation-dashboards/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Evaluation Dashboards" +short_description: "Work on evaluation dashboards for AI Product And UX." +default_prompt: "Use this skill to help with evaluation dashboards in AI Product And UX." diff --git a/skills/event-driven-agents/SKILL.md b/skills/event-driven-agents/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..2abccfa82286e142fddeff1998a1073daa4c5fd5 --- /dev/null +++ b/skills/event-driven-agents/SKILL.md @@ -0,0 +1,29 @@ +--- +name: event-driven-agents +description: "Guidance for event driven agents in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving event driven agents, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Event Driven Agents + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for event driven agents. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on event driven agents. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/event-driven-agents/agents/openai.yaml b/skills/event-driven-agents/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ef55749dd448b7732a8d4f9c3ca1c8532e3c86d9 --- /dev/null +++ b/skills/event-driven-agents/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Event Driven Agents" +short_description: "Work on event driven agents for Agentic AI." +default_prompt: "Use this skill to help with event driven agents in Agentic AI." diff --git a/skills/event-tracking/SKILL.md b/skills/event-tracking/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..7956cd7f74d92435080cf29f7e4562ea79c357e9 --- /dev/null +++ b/skills/event-tracking/SKILL.md @@ -0,0 +1,29 @@ +--- +name: event-tracking +description: "Guidance for event tracking in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving event tracking, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Event Tracking + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for event tracking. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on event tracking. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/event-tracking/agents/openai.yaml b/skills/event-tracking/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..161a2a42ba44b86c29f7a01cafe1e1a2311c5bac --- /dev/null +++ b/skills/event-tracking/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Event Tracking" +short_description: "Work on event tracking for Data Engineering." +default_prompt: "Use this skill to help with event tracking in Data Engineering." diff --git a/skills/experiment-design/SKILL.md b/skills/experiment-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..1a51ff3d50714f32252693b8df6695c2931fbe03 --- /dev/null +++ b/skills/experiment-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: experiment-design +description: "Guidance for experiment design in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving experiment design, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Experiment Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for experiment design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on experiment design. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/experiment-design/agents/openai.yaml b/skills/experiment-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9a030be91c4a3d414e04037201b718ad1dbdc413 --- /dev/null +++ b/skills/experiment-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Experiment Design" +short_description: "Work on experiment design for Research And Scientific AI." +default_prompt: "Use this skill to help with experiment design in Research And Scientific AI." diff --git a/skills/experiment-tracking/SKILL.md b/skills/experiment-tracking/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..f3d9c005d1db61bff25895075f9c8d0553924d29 --- /dev/null +++ b/skills/experiment-tracking/SKILL.md @@ -0,0 +1,29 @@ +--- +name: experiment-tracking +description: "Guidance for experiment tracking in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving experiment tracking, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# Experiment Tracking + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for experiment tracking. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on experiment tracking. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/experiment-tracking/agents/openai.yaml b/skills/experiment-tracking/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..f88f258c369863d9f8179baa73076d313bc940c3 --- /dev/null +++ b/skills/experiment-tracking/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Experiment Tracking" +short_description: "Work on experiment tracking for MLOps." +default_prompt: "Use this skill to help with experiment tracking in MLOps." diff --git a/skills/explainable-ai-ux/SKILL.md b/skills/explainable-ai-ux/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..9c3a224e666330ea6b8f4275dde38497f40f9a61 --- /dev/null +++ b/skills/explainable-ai-ux/SKILL.md @@ -0,0 +1,29 @@ +--- +name: explainable-ai-ux +description: "Guidance for explainable AI UX in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving explainable AI UX, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# Explainable AI UX + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for explainable AI UX. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on explainable AI UX. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/explainable-ai-ux/agents/openai.yaml b/skills/explainable-ai-ux/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..02b1d4de899ad3142447014755b32e8047d2b89b --- /dev/null +++ b/skills/explainable-ai-ux/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Explainable AI UX" +short_description: "Work on explainable AI UX for AI Product And UX." +default_prompt: "Use this skill to help with explainable AI UX in AI Product And UX." diff --git a/skills/face-recognition/SKILL.md b/skills/face-recognition/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..820ca26acec4f795b6bbf7156c1a0a7cc9d2f603 --- /dev/null +++ b/skills/face-recognition/SKILL.md @@ -0,0 +1,29 @@ +--- +name: face-recognition +description: "Guidance for face recognition in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving face recognition, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Face Recognition + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for face recognition. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on face recognition. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/face-recognition/agents/openai.yaml b/skills/face-recognition/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3eba3f15dc0836f24b82252f7bfc6bf3d275aa43 --- /dev/null +++ b/skills/face-recognition/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Face Recognition" +short_description: "Work on face recognition for Computer Vision." +default_prompt: "Use this skill to help with face recognition in Computer Vision." diff --git a/skills/factory-automation/SKILL.md b/skills/factory-automation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..e2cb0523cdcbd929b1416a4fba4b95b3dc10bd73 --- /dev/null +++ b/skills/factory-automation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: factory-automation +description: "Guidance for factory automation in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving factory automation, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# Factory Automation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for factory automation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on factory automation. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/factory-automation/agents/openai.yaml b/skills/factory-automation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..37b6c36894566be7247ceaf23a4eec901dd33dbc --- /dev/null +++ b/skills/factory-automation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Factory Automation" +short_description: "Work on factory automation for Robotics And IoT." +default_prompt: "Use this skill to help with factory automation in Robotics And IoT." diff --git a/skills/feature-engineering/SKILL.md b/skills/feature-engineering/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..cc3bc41e3a15b9bb54f4a159899dedf2e7c5754f --- /dev/null +++ b/skills/feature-engineering/SKILL.md @@ -0,0 +1,29 @@ +--- +name: feature-engineering +description: "Guidance for feature engineering in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving feature engineering, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Feature Engineering + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for feature engineering. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on feature engineering. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/feature-engineering/agents/openai.yaml b/skills/feature-engineering/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..4c94921ba8c6be795c6848c58cea253dd188bbe6 --- /dev/null +++ b/skills/feature-engineering/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Feature Engineering" +short_description: "Work on feature engineering for Machine Learning." +default_prompt: "Use this skill to help with feature engineering in Machine Learning." diff --git a/skills/feature-monitoring/SKILL.md b/skills/feature-monitoring/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..4c936573f42dedb5729daaa3bb991e1dff2dad65 --- /dev/null +++ b/skills/feature-monitoring/SKILL.md @@ -0,0 +1,29 @@ +--- +name: feature-monitoring +description: "Guidance for feature monitoring in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving feature monitoring, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# Feature Monitoring + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for feature monitoring. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on feature monitoring. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/feature-monitoring/agents/openai.yaml b/skills/feature-monitoring/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..0cb14cab2c29683f8a70ad402661a30649c72504 --- /dev/null +++ b/skills/feature-monitoring/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Feature Monitoring" +short_description: "Work on feature monitoring for MLOps." +default_prompt: "Use this skill to help with feature monitoring in MLOps." diff --git a/skills/feature-selection/SKILL.md b/skills/feature-selection/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..9748f1b62060ba5e99541c100faf5ee8324dcf52 --- /dev/null +++ b/skills/feature-selection/SKILL.md @@ -0,0 +1,29 @@ +--- +name: feature-selection +description: "Guidance for feature selection in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving feature selection, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Feature Selection + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for feature selection. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on feature selection. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/feature-selection/agents/openai.yaml b/skills/feature-selection/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b510c1d7ac13770a1cfc12950b3eb991ef9753e9 --- /dev/null +++ b/skills/feature-selection/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Feature Selection" +short_description: "Work on feature selection for Machine Learning." +default_prompt: "Use this skill to help with feature selection in Machine Learning." diff --git a/skills/feature-stores/SKILL.md b/skills/feature-stores/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..bb40e59aa67526403592adf7b5bfe72c23390487 --- /dev/null +++ b/skills/feature-stores/SKILL.md @@ -0,0 +1,29 @@ +--- +name: feature-stores +description: "Guidance for feature stores in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving feature stores, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Feature Stores + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for feature stores. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on feature stores. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/feature-stores/agents/openai.yaml b/skills/feature-stores/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..bbe121ed29a5ded6e929066d250a5267015509f0 --- /dev/null +++ b/skills/feature-stores/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Feature Stores" +short_description: "Work on feature stores for Data Engineering." +default_prompt: "Use this skill to help with feature stores in Data Engineering." diff --git a/skills/federated-learning-operations/SKILL.md b/skills/federated-learning-operations/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..8ea85d232515ade264c2b2d7815ea8fc51c3d35d --- /dev/null +++ b/skills/federated-learning-operations/SKILL.md @@ -0,0 +1,29 @@ +--- +name: federated-learning-operations +description: "Guidance for federated learning operations in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving federated learning operations, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# Federated Learning Operations + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for federated learning operations. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on federated learning operations. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/federated-learning-operations/agents/openai.yaml b/skills/federated-learning-operations/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..fc9e2768a17f9d892a26bc11a578b34249c48c97 --- /dev/null +++ b/skills/federated-learning-operations/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Federated Learning Operations" +short_description: "Work on federated learning operations for MLOps." +default_prompt: "Use this skill to help with federated learning operations in MLOps." diff --git a/skills/feedback-collection/SKILL.md b/skills/feedback-collection/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..4e6e44706d428cebd750b8cdc1edacd4c734b010 --- /dev/null +++ b/skills/feedback-collection/SKILL.md @@ -0,0 +1,29 @@ +--- +name: feedback-collection +description: "Guidance for feedback collection in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving feedback collection, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# Feedback Collection + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for feedback collection. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on feedback collection. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/feedback-collection/agents/openai.yaml b/skills/feedback-collection/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..83c82ef73bda9d01f3392cf74d7ff010593d48a6 --- /dev/null +++ b/skills/feedback-collection/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Feedback Collection" +short_description: "Work on feedback collection for AI Product And UX." +default_prompt: "Use this skill to help with feedback collection in AI Product And UX." diff --git a/skills/few-shot-example-design/SKILL.md b/skills/few-shot-example-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..b6f25722a13ecd63266a33ace6d51b23a2be041d --- /dev/null +++ b/skills/few-shot-example-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: few-shot-example-design +description: "Guidance for few shot example design in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving few shot example design, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# Few Shot Example Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for few shot example design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on few shot example design. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/few-shot-example-design/agents/openai.yaml b/skills/few-shot-example-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..16c422de6c87f7cb59f6416578d47a56abd7793e --- /dev/null +++ b/skills/few-shot-example-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Few Shot Example Design" +short_description: "Work on few shot example design for Prompting And Evaluation." +default_prompt: "Use this skill to help with few shot example design in Prompting And Evaluation." diff --git a/skills/file-editing-agents/SKILL.md b/skills/file-editing-agents/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..3dbf8e913d201d8eb47ed0768979df25374a40bb --- /dev/null +++ b/skills/file-editing-agents/SKILL.md @@ -0,0 +1,29 @@ +--- +name: file-editing-agents +description: "Guidance for file editing agents in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving file editing agents, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# File Editing Agents + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for file editing agents. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on file editing agents. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/file-editing-agents/agents/openai.yaml b/skills/file-editing-agents/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..2231376166a00c6b5a65288779c137a4f81e1c95 --- /dev/null +++ b/skills/file-editing-agents/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "File Editing Agents" +short_description: "Work on file editing agents for Agentic AI." +default_prompt: "Use this skill to help with file editing agents in Agentic AI." diff --git a/skills/file-upload-interfaces/SKILL.md b/skills/file-upload-interfaces/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..4a6886921f72df114f635cd1d947d81395b9f8b4 --- /dev/null +++ b/skills/file-upload-interfaces/SKILL.md @@ -0,0 +1,29 @@ +--- +name: file-upload-interfaces +description: "Guidance for file upload interfaces in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving file upload interfaces, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# File Upload Interfaces + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for file upload interfaces. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on file upload interfaces. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/file-upload-interfaces/agents/openai.yaml b/skills/file-upload-interfaces/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..1737c7e8f1dadd662546dcf57d6a0c2a92100c84 --- /dev/null +++ b/skills/file-upload-interfaces/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "File Upload Interfaces" +short_description: "Work on file upload interfaces for Web Engineering." +default_prompt: "Use this skill to help with file upload interfaces in Web Engineering." diff --git a/skills/finance-ai-workflows/SKILL.md b/skills/finance-ai-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..83195bd4e39684a8150b038fddadf23fe82e11c2 --- /dev/null +++ b/skills/finance-ai-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: finance-ai-workflows +description: "Guidance for finance AI workflows in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving finance AI workflows, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Finance AI Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for finance AI workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on finance AI workflows. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/finance-ai-workflows/agents/openai.yaml b/skills/finance-ai-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9ddcad3f0e51d5bbbd055a5f091209357e5065b5 --- /dev/null +++ b/skills/finance-ai-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Finance AI Workflows" +short_description: "Work on finance AI workflows for Domain AI." +default_prompt: "Use this skill to help with finance AI workflows in Domain AI." diff --git a/skills/financial-text-nlp/SKILL.md b/skills/financial-text-nlp/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..59856e7ae4b02b75c038d058188c0f00ed010e49 --- /dev/null +++ b/skills/financial-text-nlp/SKILL.md @@ -0,0 +1,29 @@ +--- +name: financial-text-nlp +description: "Guidance for financial text NLP in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving financial text NLP, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Financial Text NLP + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for financial text NLP. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on financial text NLP. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/financial-text-nlp/agents/openai.yaml b/skills/financial-text-nlp/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..537c9a94edee55f2d9d3442a30eda9eab77e0c0b --- /dev/null +++ b/skills/financial-text-nlp/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Financial Text NLP" +short_description: "Work on financial text NLP for Natural Language Processing." +default_prompt: "Use this skill to help with financial text NLP in Natural Language Processing." diff --git a/skills/fine-tuning-data-preparation/SKILL.md b/skills/fine-tuning-data-preparation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a30e13c732adedbd5ea2facd8e1b67c9fe079e2a --- /dev/null +++ b/skills/fine-tuning-data-preparation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: fine-tuning-data-preparation +description: "Guidance for fine tuning data preparation in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving fine tuning data preparation, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Fine Tuning Data Preparation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for fine tuning data preparation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on fine tuning data preparation. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/fine-tuning-data-preparation/agents/openai.yaml b/skills/fine-tuning-data-preparation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7a3359b15bca5491f60a1406a9d8ecd4eb49dda2 --- /dev/null +++ b/skills/fine-tuning-data-preparation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Fine Tuning Data Preparation" +short_description: "Work on fine tuning data preparation for LLM Engineering." +default_prompt: "Use this skill to help with fine tuning data preparation in LLM Engineering." diff --git a/skills/firmware-update-workflows/SKILL.md b/skills/firmware-update-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..11b912d9533ea99a3601ea6a0da7abfe8298d85b --- /dev/null +++ b/skills/firmware-update-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: firmware-update-workflows +description: "Guidance for firmware update workflows in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving firmware update workflows, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# Firmware Update Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for firmware update workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on firmware update workflows. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/firmware-update-workflows/agents/openai.yaml b/skills/firmware-update-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..935cece25528d32c97e5e04e46fb0747cab3b84a --- /dev/null +++ b/skills/firmware-update-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Firmware Update Workflows" +short_description: "Work on firmware update workflows for Robotics And IoT." +default_prompt: "Use this skill to help with firmware update workflows in Robotics And IoT." diff --git a/skills/fleet-monitoring/SKILL.md b/skills/fleet-monitoring/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..f7780312ca8f5e7a8be60318f85f2d71f0b77941 --- /dev/null +++ b/skills/fleet-monitoring/SKILL.md @@ -0,0 +1,29 @@ +--- +name: fleet-monitoring +description: "Guidance for fleet monitoring in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving fleet monitoring, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# Fleet Monitoring + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for fleet monitoring. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on fleet monitoring. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/fleet-monitoring/agents/openai.yaml b/skills/fleet-monitoring/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..f52564d9881719d001362e43c8ff359e427d33ed --- /dev/null +++ b/skills/fleet-monitoring/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Fleet Monitoring" +short_description: "Work on fleet monitoring for Robotics And IoT." +default_prompt: "Use this skill to help with fleet monitoring in Robotics And IoT." diff --git a/skills/flutter-apps/SKILL.md b/skills/flutter-apps/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..689d84110f4af2b583072ad9d4d3c4030ea74429 --- /dev/null +++ b/skills/flutter-apps/SKILL.md @@ -0,0 +1,29 @@ +--- +name: flutter-apps +description: "Guidance for Flutter apps in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving Flutter apps, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Flutter Apps + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for Flutter apps. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on Flutter apps. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/flutter-apps/agents/openai.yaml b/skills/flutter-apps/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ace852c11e34d70b61eef0bd9612de92b0ea8189 --- /dev/null +++ b/skills/flutter-apps/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Flutter Apps" +short_description: "Work on Flutter apps for Mobile App Engineering." +default_prompt: "Use this skill to help with Flutter apps in Mobile App Engineering." diff --git a/skills/form-validation/SKILL.md b/skills/form-validation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..7d20cef5d440299dcf2daa3adcc75dba02afc019 --- /dev/null +++ b/skills/form-validation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: form-validation +description: "Guidance for form validation in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving form validation, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Form Validation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for form validation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on form validation. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/form-validation/agents/openai.yaml b/skills/form-validation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..8dbe77efa36197b98bfd6f2bf7bbb5640ea783de --- /dev/null +++ b/skills/form-validation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Form Validation" +short_description: "Work on form validation for Web Engineering." +default_prompt: "Use this skill to help with form validation in Web Engineering." diff --git a/skills/frontend-error-monitoring/SKILL.md b/skills/frontend-error-monitoring/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..d94bf1bab9bcd95e4e873fe99263706d6c1066b0 --- /dev/null +++ b/skills/frontend-error-monitoring/SKILL.md @@ -0,0 +1,29 @@ +--- +name: frontend-error-monitoring +description: "Guidance for frontend error monitoring in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving frontend error monitoring, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Frontend Error Monitoring + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for frontend error monitoring. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on frontend error monitoring. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/frontend-error-monitoring/agents/openai.yaml b/skills/frontend-error-monitoring/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d919a6204e397c48f895650e54285ac58858e8b4 --- /dev/null +++ b/skills/frontend-error-monitoring/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Frontend Error Monitoring" +short_description: "Work on frontend error monitoring for Web Engineering." +default_prompt: "Use this skill to help with frontend error monitoring in Web Engineering." diff --git a/skills/function-routing/SKILL.md b/skills/function-routing/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..4cad170bde5f2df266eb2b0047900a8fd175c83e --- /dev/null +++ b/skills/function-routing/SKILL.md @@ -0,0 +1,29 @@ +--- +name: function-routing +description: "Guidance for function routing in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving function routing, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Function Routing + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for function routing. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on function routing. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/function-routing/agents/openai.yaml b/skills/function-routing/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..54198ade1433ed2deade85be83b66dfbadeb545f --- /dev/null +++ b/skills/function-routing/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Function Routing" +short_description: "Work on function routing for LLM Engineering." +default_prompt: "Use this skill to help with function routing in LLM Engineering." diff --git a/skills/funnel-analysis/SKILL.md b/skills/funnel-analysis/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..c67d16777e7d1cc31cf4dc08dfc967cbf5b35864 --- /dev/null +++ b/skills/funnel-analysis/SKILL.md @@ -0,0 +1,29 @@ +--- +name: funnel-analysis +description: "Guidance for funnel analysis in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving funnel analysis, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# Funnel Analysis + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for funnel analysis. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on funnel analysis. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/funnel-analysis/agents/openai.yaml b/skills/funnel-analysis/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e362d47ca149e2c1aac6a712c0adf7a6044f7402 --- /dev/null +++ b/skills/funnel-analysis/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Funnel Analysis" +short_description: "Work on funnel analysis for Databases And Analytics." +default_prompt: "Use this skill to help with funnel analysis in Databases And Analytics." diff --git a/skills/gaming-ai-workflows/SKILL.md b/skills/gaming-ai-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..244e606b2660dfa10bd1c0aa0904cf92807f9dfa --- /dev/null +++ b/skills/gaming-ai-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: gaming-ai-workflows +description: "Guidance for gaming AI workflows in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving gaming AI workflows, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Gaming AI Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for gaming AI workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on gaming AI workflows. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/gaming-ai-workflows/agents/openai.yaml b/skills/gaming-ai-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..bfbaf6dc3220eeac4accc3d70144e99abc551aa2 --- /dev/null +++ b/skills/gaming-ai-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Gaming AI Workflows" +short_description: "Work on gaming AI workflows for Domain AI." +default_prompt: "Use this skill to help with gaming AI workflows in Domain AI." diff --git a/skills/gan-training/SKILL.md b/skills/gan-training/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..1fdc1c69762051fbf543965955ef6a1b102d0610 --- /dev/null +++ b/skills/gan-training/SKILL.md @@ -0,0 +1,29 @@ +--- +name: gan-training +description: "Guidance for GAN training in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving GAN training, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# GAN Training + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for GAN training. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on GAN training. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/gan-training/agents/openai.yaml b/skills/gan-training/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..eb41397ac63c346cf29a3ad9360222362c00bf71 --- /dev/null +++ b/skills/gan-training/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "GAN Training" +short_description: "Work on GAN training for Deep Learning." +default_prompt: "Use this skill to help with GAN training in Deep Learning." diff --git a/skills/geospatial-ml/SKILL.md b/skills/geospatial-ml/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..631910d8eb483f5bd90396559852ffa32ef01c54 --- /dev/null +++ b/skills/geospatial-ml/SKILL.md @@ -0,0 +1,29 @@ +--- +name: geospatial-ml +description: "Guidance for geospatial ML in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving geospatial ML, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Geospatial ML + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for geospatial ML. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on geospatial ML. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/geospatial-ml/agents/openai.yaml b/skills/geospatial-ml/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..0d4cb2fdd3dcdcaa272e71c0edc1c10beeb0b946 --- /dev/null +++ b/skills/geospatial-ml/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Geospatial ML" +short_description: "Work on geospatial ML for Research And Scientific AI." +default_prompt: "Use this skill to help with geospatial ML in Research And Scientific AI." diff --git a/skills/geospatial-multimodal-analysis/SKILL.md b/skills/geospatial-multimodal-analysis/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..62c51ea14b4f27432429d186cb6e36d76c202aa8 --- /dev/null +++ b/skills/geospatial-multimodal-analysis/SKILL.md @@ -0,0 +1,29 @@ +--- +name: geospatial-multimodal-analysis +description: "Guidance for geospatial multimodal analysis in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving geospatial multimodal analysis, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Geospatial Multimodal Analysis + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for geospatial multimodal analysis. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on geospatial multimodal analysis. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/geospatial-multimodal-analysis/agents/openai.yaml b/skills/geospatial-multimodal-analysis/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..500fe8ff602a5918bfb3723000405701f5afa57c --- /dev/null +++ b/skills/geospatial-multimodal-analysis/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Geospatial Multimodal Analysis" +short_description: "Work on geospatial multimodal analysis for Multimodal AI." +default_prompt: "Use this skill to help with geospatial multimodal analysis in Multimodal AI." diff --git a/skills/goal-tracking/SKILL.md b/skills/goal-tracking/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..b4ee3ad908dd14efa24096c2163263f5a640fba0 --- /dev/null +++ b/skills/goal-tracking/SKILL.md @@ -0,0 +1,29 @@ +--- +name: goal-tracking +description: "Guidance for goal tracking in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving goal tracking, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Goal Tracking + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for goal tracking. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on goal tracking. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/goal-tracking/agents/openai.yaml b/skills/goal-tracking/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..a2ab2472748d3c70d25337889b5a2738b1c4a144 --- /dev/null +++ b/skills/goal-tracking/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Goal Tracking" +short_description: "Work on goal tracking for Agentic AI." +default_prompt: "Use this skill to help with goal tracking in Agentic AI." diff --git a/skills/golden-answer-datasets/SKILL.md b/skills/golden-answer-datasets/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..230bfe62fc97339b6e58cb6a59026a5716ae387e --- /dev/null +++ b/skills/golden-answer-datasets/SKILL.md @@ -0,0 +1,29 @@ +--- +name: golden-answer-datasets +description: "Guidance for golden answer datasets in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving golden answer datasets, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# Golden Answer Datasets + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for golden answer datasets. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on golden answer datasets. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/golden-answer-datasets/agents/openai.yaml b/skills/golden-answer-datasets/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..dd3fe0a9d581829e46d92752ab393ed9ec2cc7b2 --- /dev/null +++ b/skills/golden-answer-datasets/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Golden Answer Datasets" +short_description: "Work on golden answer datasets for Prompting And Evaluation." +default_prompt: "Use this skill to help with golden answer datasets in Prompting And Evaluation." diff --git a/skills/governed-self-service-analytics/SKILL.md b/skills/governed-self-service-analytics/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..e781d9e465f72d49ecd2bc346298ec3561013e00 --- /dev/null +++ b/skills/governed-self-service-analytics/SKILL.md @@ -0,0 +1,29 @@ +--- +name: governed-self-service-analytics +description: "Guidance for governed self service analytics in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving governed self service analytics, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# Governed Self Service Analytics + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for governed self service analytics. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on governed self service analytics. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/governed-self-service-analytics/agents/openai.yaml b/skills/governed-self-service-analytics/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..42c6ea00f0478713b857fee76be610db47d6d604 --- /dev/null +++ b/skills/governed-self-service-analytics/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Governed Self Service Analytics" +short_description: "Work on governed self service analytics for Databases And Analytics." +default_prompt: "Use this skill to help with governed self service analytics in Databases And Analytics." diff --git a/skills/gpu-job-scheduling/SKILL.md b/skills/gpu-job-scheduling/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a894aa0c26bf0a6cab2aec85f2e884d26651027b --- /dev/null +++ b/skills/gpu-job-scheduling/SKILL.md @@ -0,0 +1,29 @@ +--- +name: gpu-job-scheduling +description: "Guidance for GPU job scheduling in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving GPU job scheduling, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# GPU Job Scheduling + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for GPU job scheduling. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on GPU job scheduling. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/gpu-job-scheduling/agents/openai.yaml b/skills/gpu-job-scheduling/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b3529ccd38dce55737bfdc45a0a9e8605644838e --- /dev/null +++ b/skills/gpu-job-scheduling/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "GPU Job Scheduling" +short_description: "Work on GPU job scheduling for MLOps." +default_prompt: "Use this skill to help with GPU job scheduling in MLOps." diff --git a/skills/gpu-memory-debugging/SKILL.md b/skills/gpu-memory-debugging/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..8490ffafef69c0c0e80011674470c69ead9b3ee7 --- /dev/null +++ b/skills/gpu-memory-debugging/SKILL.md @@ -0,0 +1,29 @@ +--- +name: gpu-memory-debugging +description: "Guidance for GPU memory debugging in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving GPU memory debugging, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# GPU Memory Debugging + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for GPU memory debugging. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on GPU memory debugging. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/gpu-memory-debugging/agents/openai.yaml b/skills/gpu-memory-debugging/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..c9398b0982ba7393f5eaa1eb52f2f62365dfc830 --- /dev/null +++ b/skills/gpu-memory-debugging/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "GPU Memory Debugging" +short_description: "Work on GPU memory debugging for Deep Learning." +default_prompt: "Use this skill to help with GPU memory debugging in Deep Learning." diff --git a/skills/gradient-checkpointing/SKILL.md b/skills/gradient-checkpointing/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..47cff9dcb186eec4dbb15a93d90b5b7c0f4977c9 --- /dev/null +++ b/skills/gradient-checkpointing/SKILL.md @@ -0,0 +1,29 @@ +--- +name: gradient-checkpointing +description: "Guidance for gradient checkpointing in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving gradient checkpointing, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Gradient Checkpointing + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for gradient checkpointing. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on gradient checkpointing. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/gradient-checkpointing/agents/openai.yaml b/skills/gradient-checkpointing/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..fd8f5f2042b7a4923619a364de6e8890b008df58 --- /dev/null +++ b/skills/gradient-checkpointing/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Gradient Checkpointing" +short_description: "Work on gradient checkpointing for Deep Learning." +default_prompt: "Use this skill to help with gradient checkpointing in Deep Learning." diff --git a/skills/grant-proposal-technical-review/SKILL.md b/skills/grant-proposal-technical-review/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..f37c13374ac194b04390f6fb3fad8d303f0bed47 --- /dev/null +++ b/skills/grant-proposal-technical-review/SKILL.md @@ -0,0 +1,29 @@ +--- +name: grant-proposal-technical-review +description: "Guidance for grant proposal technical review in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving grant proposal technical review, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Grant Proposal Technical Review + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for grant proposal technical review. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on grant proposal technical review. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/grant-proposal-technical-review/agents/openai.yaml b/skills/grant-proposal-technical-review/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..8a96715e8e99db7c7642d8dcdab8b45b5e353afe --- /dev/null +++ b/skills/grant-proposal-technical-review/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Grant Proposal Technical Review" +short_description: "Work on grant proposal technical review for Research And Scientific AI." +default_prompt: "Use this skill to help with grant proposal technical review in Research And Scientific AI." diff --git a/skills/graph-database-modeling/SKILL.md b/skills/graph-database-modeling/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..fadd462a15c3e8a6d1fb7ffdf5844bf78419efc1 --- /dev/null +++ b/skills/graph-database-modeling/SKILL.md @@ -0,0 +1,29 @@ +--- +name: graph-database-modeling +description: "Guidance for graph database modeling in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving graph database modeling, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# Graph Database Modeling + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for graph database modeling. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on graph database modeling. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/graph-database-modeling/agents/openai.yaml b/skills/graph-database-modeling/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..140db71e4c36b2e7040f576c37691ff12f3a1bda --- /dev/null +++ b/skills/graph-database-modeling/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Graph Database Modeling" +short_description: "Work on graph database modeling for Databases And Analytics." +default_prompt: "Use this skill to help with graph database modeling in Databases And Analytics." diff --git a/skills/groundedness-scoring/SKILL.md b/skills/groundedness-scoring/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a8dceb85a376e4d65e1ab943fe45d4aaec7c091a --- /dev/null +++ b/skills/groundedness-scoring/SKILL.md @@ -0,0 +1,29 @@ +--- +name: groundedness-scoring +description: "Guidance for groundedness scoring in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving groundedness scoring, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# Groundedness Scoring + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for groundedness scoring. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on groundedness scoring. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/groundedness-scoring/agents/openai.yaml b/skills/groundedness-scoring/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..09cd31aa94fe28346cc093e3c83d978ef6b4ddb3 --- /dev/null +++ b/skills/groundedness-scoring/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Groundedness Scoring" +short_description: "Work on groundedness scoring for Prompting And Evaluation." +default_prompt: "Use this skill to help with groundedness scoring in Prompting And Evaluation." diff --git a/skills/hallucination-measurement/SKILL.md b/skills/hallucination-measurement/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..4efbe2fe6fa9e45b5bade52189832f4d39657251 --- /dev/null +++ b/skills/hallucination-measurement/SKILL.md @@ -0,0 +1,29 @@ +--- +name: hallucination-measurement +description: "Guidance for hallucination measurement in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving hallucination measurement, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# Hallucination Measurement + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for hallucination measurement. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on hallucination measurement. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/hallucination-measurement/agents/openai.yaml b/skills/hallucination-measurement/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d1020659549f9181a0dc80e2fdb2998828c20a48 --- /dev/null +++ b/skills/hallucination-measurement/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Hallucination Measurement" +short_description: "Work on hallucination measurement for Prompting And Evaluation." +default_prompt: "Use this skill to help with hallucination measurement in Prompting And Evaluation." diff --git a/skills/hardware-in-the-loop-tests/SKILL.md b/skills/hardware-in-the-loop-tests/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..f96d041a68c1b6b109c48bb77fca233176f190c1 --- /dev/null +++ b/skills/hardware-in-the-loop-tests/SKILL.md @@ -0,0 +1,29 @@ +--- +name: hardware-in-the-loop-tests +description: "Guidance for hardware in the loop tests in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving hardware in the loop tests, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# Hardware In The Loop Tests + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for hardware in the loop tests. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on hardware in the loop tests. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/hardware-in-the-loop-tests/agents/openai.yaml b/skills/hardware-in-the-loop-tests/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7e4cb0531ab1435ab40c80358941c663259c81c8 --- /dev/null +++ b/skills/hardware-in-the-loop-tests/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Hardware In The Loop Tests" +short_description: "Work on hardware in the loop tests for Robotics And IoT." +default_prompt: "Use this skill to help with hardware in the loop tests in Robotics And IoT." diff --git a/skills/healthcare-ai-workflows/SKILL.md b/skills/healthcare-ai-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..d49f187acde672a109e4b6e8d7b5d1d5880a7474 --- /dev/null +++ b/skills/healthcare-ai-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: healthcare-ai-workflows +description: "Guidance for healthcare AI workflows in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving healthcare AI workflows, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Healthcare AI Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for healthcare AI workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on healthcare AI workflows. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/healthcare-ai-workflows/agents/openai.yaml b/skills/healthcare-ai-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..734a008bd57863d1b85af28efc6ef4b8841e5c72 --- /dev/null +++ b/skills/healthcare-ai-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Healthcare AI Workflows" +short_description: "Work on healthcare AI workflows for Domain AI." +default_prompt: "Use this skill to help with healthcare AI workflows in Domain AI." diff --git a/skills/hr-ai-workflows/SKILL.md b/skills/hr-ai-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..b36aa65a3fa52f4aaa0448568c197fec808b8b76 --- /dev/null +++ b/skills/hr-ai-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: hr-ai-workflows +description: "Guidance for HR AI workflows in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving HR AI workflows, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# HR AI Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for HR AI workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on HR AI workflows. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/hr-ai-workflows/agents/openai.yaml b/skills/hr-ai-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..878bd1ccf37918e1a271bad2413e34a0d6d05844 --- /dev/null +++ b/skills/hr-ai-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "HR AI Workflows" +short_description: "Work on HR AI workflows for Domain AI." +default_prompt: "Use this skill to help with HR AI workflows in Domain AI." diff --git a/skills/human-in-the-loop-review/SKILL.md b/skills/human-in-the-loop-review/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..7d7f3327cbdbc0af3f4dac62ed644fcf3a9dd0d0 --- /dev/null +++ b/skills/human-in-the-loop-review/SKILL.md @@ -0,0 +1,29 @@ +--- +name: human-in-the-loop-review +description: "Guidance for human in the loop review in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving human in the loop review, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Human In The Loop Review + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for human in the loop review. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on human in the loop review. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/human-in-the-loop-review/agents/openai.yaml b/skills/human-in-the-loop-review/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..1bf49fe7572241a1a3cabbf4f039bdbf31d14a8f --- /dev/null +++ b/skills/human-in-the-loop-review/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Human In The Loop Review" +short_description: "Work on human in the loop review for Agentic AI." +default_prompt: "Use this skill to help with human in the loop review in Agentic AI." diff --git a/skills/human-review-queues/SKILL.md b/skills/human-review-queues/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..99ec5d142e7ec809378c1cc11ff71af39b3af7b1 --- /dev/null +++ b/skills/human-review-queues/SKILL.md @@ -0,0 +1,29 @@ +--- +name: human-review-queues +description: "Guidance for human review queues in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving human review queues, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# Human Review Queues + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for human review queues. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on human review queues. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/human-review-queues/agents/openai.yaml b/skills/human-review-queues/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3c5912ab39f5e3a967e614d5b7733ee5e04bf479 --- /dev/null +++ b/skills/human-review-queues/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Human Review Queues" +short_description: "Work on human review queues for AI Product And UX." +default_prompt: "Use this skill to help with human review queues in AI Product And UX." diff --git a/skills/hyperparameter-optimization/SKILL.md b/skills/hyperparameter-optimization/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..4ad77ab975c52ff40cc08e7592a95d552c62835c --- /dev/null +++ b/skills/hyperparameter-optimization/SKILL.md @@ -0,0 +1,29 @@ +--- +name: hyperparameter-optimization +description: "Guidance for hyperparameter optimization in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving hyperparameter optimization, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Hyperparameter Optimization + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for hyperparameter optimization. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on hyperparameter optimization. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/hyperparameter-optimization/agents/openai.yaml b/skills/hyperparameter-optimization/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..25a962c380c4f91b7a5e4a4a8f3c724d81aa7a7f --- /dev/null +++ b/skills/hyperparameter-optimization/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Hyperparameter Optimization" +short_description: "Work on hyperparameter optimization for Machine Learning." +default_prompt: "Use this skill to help with hyperparameter optimization in Machine Learning." diff --git a/skills/iam-policy-design/SKILL.md b/skills/iam-policy-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..368115266bea2f9a4647cad39d79408ff80d7099 --- /dev/null +++ b/skills/iam-policy-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: iam-policy-design +description: "Guidance for IAM policy design in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving IAM policy design, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# IAM Policy Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for IAM policy design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on IAM policy design. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/iam-policy-design/agents/openai.yaml b/skills/iam-policy-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..54b593a57bc71444df620bcdeed523795ad08d07 --- /dev/null +++ b/skills/iam-policy-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "IAM Policy Design" +short_description: "Work on IAM policy design for Cloud And DevOps." +default_prompt: "Use this skill to help with IAM policy design in Cloud And DevOps." diff --git a/skills/idempotent-jobs/SKILL.md b/skills/idempotent-jobs/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..906836d9cb40b9a31acb20f81f40b4b892f65b8b --- /dev/null +++ b/skills/idempotent-jobs/SKILL.md @@ -0,0 +1,29 @@ +--- +name: idempotent-jobs +description: "Guidance for idempotent jobs in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving idempotent jobs, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Idempotent Jobs + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for idempotent jobs. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on idempotent jobs. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/idempotent-jobs/agents/openai.yaml b/skills/idempotent-jobs/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..a254deafc289911661274a74106a8e5ea0a37991 --- /dev/null +++ b/skills/idempotent-jobs/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Idempotent Jobs" +short_description: "Work on idempotent jobs for Data Engineering." +default_prompt: "Use this skill to help with idempotent jobs in Data Engineering." diff --git a/skills/image-augmentation/SKILL.md b/skills/image-augmentation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..1a96ff23403568fe7b2e538f577b9461a860e5e7 --- /dev/null +++ b/skills/image-augmentation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: image-augmentation +description: "Guidance for image augmentation in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving image augmentation, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Image Augmentation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for image augmentation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on image augmentation. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/image-augmentation/agents/openai.yaml b/skills/image-augmentation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..cdf89bd2fa8ba729b30163732aa257c5af3b1835 --- /dev/null +++ b/skills/image-augmentation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Image Augmentation" +short_description: "Work on image augmentation for Computer Vision." +default_prompt: "Use this skill to help with image augmentation in Computer Vision." diff --git a/skills/image-captioning/SKILL.md b/skills/image-captioning/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..0ca210bae0bb6bfd6b6294ebb8c820a5597bf577 --- /dev/null +++ b/skills/image-captioning/SKILL.md @@ -0,0 +1,29 @@ +--- +name: image-captioning +description: "Guidance for image captioning in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving image captioning, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Image Captioning + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for image captioning. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on image captioning. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/image-captioning/agents/openai.yaml b/skills/image-captioning/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..6c6aacb49b04d2ea8fcfc262310e61e429e6b078 --- /dev/null +++ b/skills/image-captioning/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Image Captioning" +short_description: "Work on image captioning for Computer Vision." +default_prompt: "Use this skill to help with image captioning in Computer Vision." diff --git a/skills/image-classification/SKILL.md b/skills/image-classification/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..3e083cb71d4e6fa2aa96e0763b603d0c5a04273d --- /dev/null +++ b/skills/image-classification/SKILL.md @@ -0,0 +1,29 @@ +--- +name: image-classification +description: "Guidance for image classification in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving image classification, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Image Classification + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for image classification. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on image classification. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/image-classification/agents/openai.yaml b/skills/image-classification/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..37a4059e3b3ff6ed9bcbe329dc91802ba638889d --- /dev/null +++ b/skills/image-classification/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Image Classification" +short_description: "Work on image classification for Computer Vision." +default_prompt: "Use this skill to help with image classification in Computer Vision." diff --git a/skills/image-editing-workflows/SKILL.md b/skills/image-editing-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..69cd0b352fe301f5785f1abc58c209f6ae71ffde --- /dev/null +++ b/skills/image-editing-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: image-editing-workflows +description: "Guidance for image editing workflows in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving image editing workflows, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Image Editing Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for image editing workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on image editing workflows. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/image-editing-workflows/agents/openai.yaml b/skills/image-editing-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..8b2ed91b3f94a557f33fee23d295456fd546b51f --- /dev/null +++ b/skills/image-editing-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Image Editing Workflows" +short_description: "Work on image editing workflows for Multimodal AI." +default_prompt: "Use this skill to help with image editing workflows in Multimodal AI." diff --git a/skills/image-generation-prompting/SKILL.md b/skills/image-generation-prompting/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..5b5d8b57d543bff44f5361f06352ceedd96d78f1 --- /dev/null +++ b/skills/image-generation-prompting/SKILL.md @@ -0,0 +1,29 @@ +--- +name: image-generation-prompting +description: "Guidance for image generation prompting in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving image generation prompting, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Image Generation Prompting + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for image generation prompting. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on image generation prompting. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/image-generation-prompting/agents/openai.yaml b/skills/image-generation-prompting/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..8b81cf394b609dc9acae95e50b4b27b86afca798 --- /dev/null +++ b/skills/image-generation-prompting/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Image Generation Prompting" +short_description: "Work on image generation prompting for Multimodal AI." +default_prompt: "Use this skill to help with image generation prompting in Multimodal AI." diff --git a/skills/image-grounded-chat/SKILL.md b/skills/image-grounded-chat/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..29b278c1ffd9eb717f561e6788522eecb186b437 --- /dev/null +++ b/skills/image-grounded-chat/SKILL.md @@ -0,0 +1,29 @@ +--- +name: image-grounded-chat +description: "Guidance for image grounded chat in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving image grounded chat, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Image Grounded Chat + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for image grounded chat. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on image grounded chat. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/image-grounded-chat/agents/openai.yaml b/skills/image-grounded-chat/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..f1bd83302f7ddd60a69a612ada1edd0a014d2876 --- /dev/null +++ b/skills/image-grounded-chat/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Image Grounded Chat" +short_description: "Work on image grounded chat for Multimodal AI." +default_prompt: "Use this skill to help with image grounded chat in Multimodal AI." diff --git a/skills/image-quality-assessment/SKILL.md b/skills/image-quality-assessment/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a47904026f0526f284230cd94a3cb4772e0d9315 --- /dev/null +++ b/skills/image-quality-assessment/SKILL.md @@ -0,0 +1,29 @@ +--- +name: image-quality-assessment +description: "Guidance for image quality assessment in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving image quality assessment, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Image Quality Assessment + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for image quality assessment. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on image quality assessment. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/image-quality-assessment/agents/openai.yaml b/skills/image-quality-assessment/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ecd404afe1f5b5bf55f45bb269d74ab269eb42ef --- /dev/null +++ b/skills/image-quality-assessment/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Image Quality Assessment" +short_description: "Work on image quality assessment for Computer Vision." +default_prompt: "Use this skill to help with image quality assessment in Computer Vision." diff --git a/skills/in-app-purchases/SKILL.md b/skills/in-app-purchases/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..d521904c7d0baba882cf370d8af07d2574ff4301 --- /dev/null +++ b/skills/in-app-purchases/SKILL.md @@ -0,0 +1,29 @@ +--- +name: in-app-purchases +description: "Guidance for in app purchases in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving in app purchases, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# In App Purchases + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for in app purchases. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on in app purchases. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/in-app-purchases/agents/openai.yaml b/skills/in-app-purchases/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ea819fb0950c4c518884e954d39d639c14482dbb --- /dev/null +++ b/skills/in-app-purchases/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "In App Purchases" +short_description: "Work on in app purchases for Mobile App Engineering." +default_prompt: "Use this skill to help with in app purchases in Mobile App Engineering." diff --git a/skills/incident-response-agents/SKILL.md b/skills/incident-response-agents/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..157693c77a909ac104b231abf53e8ae91bc1c524 --- /dev/null +++ b/skills/incident-response-agents/SKILL.md @@ -0,0 +1,29 @@ +--- +name: incident-response-agents +description: "Guidance for incident response agents in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving incident response agents, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Incident Response Agents + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for incident response agents. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on incident response agents. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/incident-response-agents/agents/openai.yaml b/skills/incident-response-agents/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..c79fe54e882352b2d9bcb46a1714639866dee240 --- /dev/null +++ b/skills/incident-response-agents/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Incident Response Agents" +short_description: "Work on incident response agents for Agentic AI." +default_prompt: "Use this skill to help with incident response agents in Agentic AI." diff --git a/skills/incident-response/SKILL.md b/skills/incident-response/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..ab646c8c0e94e0084c53955f2673822628553410 --- /dev/null +++ b/skills/incident-response/SKILL.md @@ -0,0 +1,29 @@ +--- +name: incident-response +description: "Guidance for incident response in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving incident response, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# Incident Response + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for incident response. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on incident response. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/incident-response/agents/openai.yaml b/skills/incident-response/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b80a8921ed5b9009c1cef703a6fe49aff9ff8d91 --- /dev/null +++ b/skills/incident-response/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Incident Response" +short_description: "Work on incident response for Cloud And DevOps." +default_prompt: "Use this skill to help with incident response in Cloud And DevOps." diff --git a/skills/incident-runbooks/SKILL.md b/skills/incident-runbooks/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..ad0a5d7a3980e2f84daaa89fcd2dbb889ab53096 --- /dev/null +++ b/skills/incident-runbooks/SKILL.md @@ -0,0 +1,29 @@ +--- +name: incident-runbooks +description: "Guidance for incident runbooks in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving incident runbooks, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# Incident Runbooks + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for incident runbooks. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on incident runbooks. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/incident-runbooks/agents/openai.yaml b/skills/incident-runbooks/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..fd2e26a63c22d067df2aba41ca18c7a344764ed0 --- /dev/null +++ b/skills/incident-runbooks/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Incident Runbooks" +short_description: "Work on incident runbooks for MLOps." +default_prompt: "Use this skill to help with incident runbooks in MLOps." diff --git a/skills/incremental-models/SKILL.md b/skills/incremental-models/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..4de842248af10db51681fdbb05649cc675a518b4 --- /dev/null +++ b/skills/incremental-models/SKILL.md @@ -0,0 +1,29 @@ +--- +name: incremental-models +description: "Guidance for incremental models in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving incremental models, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Incremental Models + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for incremental models. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on incremental models. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/incremental-models/agents/openai.yaml b/skills/incremental-models/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..06d02d23f203ee14488b733643521a0715c0d7ff --- /dev/null +++ b/skills/incremental-models/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Incremental Models" +short_description: "Work on incremental models for Data Engineering." +default_prompt: "Use this skill to help with incremental models in Data Engineering." diff --git a/skills/index-tuning/SKILL.md b/skills/index-tuning/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..e2db5600babb3b9c15ffeccc44a91d3562a25c3d --- /dev/null +++ b/skills/index-tuning/SKILL.md @@ -0,0 +1,29 @@ +--- +name: index-tuning +description: "Guidance for index tuning in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving index tuning, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# Index Tuning + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for index tuning. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on index tuning. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/index-tuning/agents/openai.yaml b/skills/index-tuning/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..59a68ddba85833ba021171cd86cf352e67270173 --- /dev/null +++ b/skills/index-tuning/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Index Tuning" +short_description: "Work on index tuning for Databases And Analytics." +default_prompt: "Use this skill to help with index tuning in Databases And Analytics." diff --git a/skills/industrial-vision/SKILL.md b/skills/industrial-vision/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..d44c66d9bfd89f25dee38b69b13b8311cfba4acf --- /dev/null +++ b/skills/industrial-vision/SKILL.md @@ -0,0 +1,29 @@ +--- +name: industrial-vision +description: "Guidance for industrial vision in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving industrial vision, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# Industrial Vision + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for industrial vision. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on industrial vision. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/industrial-vision/agents/openai.yaml b/skills/industrial-vision/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..86e9777310b4f9287149d3b99cf7a01793255e46 --- /dev/null +++ b/skills/industrial-vision/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Industrial Vision" +short_description: "Work on industrial vision for Robotics And IoT." +default_prompt: "Use this skill to help with industrial vision in Robotics And IoT." diff --git a/skills/inference-deployment/SKILL.md b/skills/inference-deployment/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..4e050a95129ced33002d124266f19fc66ab8319e --- /dev/null +++ b/skills/inference-deployment/SKILL.md @@ -0,0 +1,29 @@ +--- +name: inference-deployment +description: "Guidance for inference deployment in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving inference deployment, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# Inference Deployment + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for inference deployment. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on inference deployment. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/inference-deployment/agents/openai.yaml b/skills/inference-deployment/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ecdd99e524661545e104234dee817fbadf9b0680 --- /dev/null +++ b/skills/inference-deployment/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Inference Deployment" +short_description: "Work on inference deployment for MLOps." +default_prompt: "Use this skill to help with inference deployment in MLOps." diff --git a/skills/infrastructure-as-code/SKILL.md b/skills/infrastructure-as-code/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..4ed47e690d7caecb6da21590df5a2d28b9a6f169 --- /dev/null +++ b/skills/infrastructure-as-code/SKILL.md @@ -0,0 +1,29 @@ +--- +name: infrastructure-as-code +description: "Guidance for infrastructure as code in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving infrastructure as code, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# Infrastructure As Code + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for infrastructure as code. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on infrastructure as code. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/infrastructure-as-code/agents/openai.yaml b/skills/infrastructure-as-code/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..0cfee57586c81646e3c8ca4753b0ece6bfb42530 --- /dev/null +++ b/skills/infrastructure-as-code/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Infrastructure As Code" +short_description: "Work on infrastructure as code for Cloud And DevOps." +default_prompt: "Use this skill to help with infrastructure as code in Cloud And DevOps." diff --git a/skills/input-validation/SKILL.md b/skills/input-validation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..57ee64d139245e9ec3b9e5fa0ea23243167fb27d --- /dev/null +++ b/skills/input-validation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: input-validation +description: "Guidance for input validation in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving input validation, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# Input Validation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for input validation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on input validation. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/input-validation/agents/openai.yaml b/skills/input-validation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..a7811eb604b323342a07436c6c546e0682073cb9 --- /dev/null +++ b/skills/input-validation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Input Validation" +short_description: "Work on input validation for Security And Privacy." +default_prompt: "Use this skill to help with input validation in Security And Privacy." diff --git a/skills/instance-segmentation/SKILL.md b/skills/instance-segmentation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..9eec54dfa7adb8bb3aede5f2cfa559c3fd4fd275 --- /dev/null +++ b/skills/instance-segmentation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: instance-segmentation +description: "Guidance for instance segmentation in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving instance segmentation, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Instance Segmentation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for instance segmentation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on instance segmentation. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/instance-segmentation/agents/openai.yaml b/skills/instance-segmentation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9da70cdc3e7937caa8b403c45873af687405f9e4 --- /dev/null +++ b/skills/instance-segmentation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Instance Segmentation" +short_description: "Work on instance segmentation for Computer Vision." +default_prompt: "Use this skill to help with instance segmentation in Computer Vision." diff --git a/skills/instruction-dataset-curation/SKILL.md b/skills/instruction-dataset-curation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a8adfbc685536a9737558ab86931f0a9f0166706 --- /dev/null +++ b/skills/instruction-dataset-curation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: instruction-dataset-curation +description: "Guidance for instruction dataset curation in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving instruction dataset curation, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Instruction Dataset Curation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for instruction dataset curation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on instruction dataset curation. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/instruction-dataset-curation/agents/openai.yaml b/skills/instruction-dataset-curation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..68b879646478dff40462d7f385f90c12357f0178 --- /dev/null +++ b/skills/instruction-dataset-curation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Instruction Dataset Curation" +short_description: "Work on instruction dataset curation for LLM Engineering." +default_prompt: "Use this skill to help with instruction dataset curation in LLM Engineering." diff --git a/skills/instruction-hierarchy-checks/SKILL.md b/skills/instruction-hierarchy-checks/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..5943eb80f930ddad1042a1175e72165b44a680d9 --- /dev/null +++ b/skills/instruction-hierarchy-checks/SKILL.md @@ -0,0 +1,29 @@ +--- +name: instruction-hierarchy-checks +description: "Guidance for instruction hierarchy checks in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving instruction hierarchy checks, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# Instruction Hierarchy Checks + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for instruction hierarchy checks. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on instruction hierarchy checks. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/instruction-hierarchy-checks/agents/openai.yaml b/skills/instruction-hierarchy-checks/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..f247cc31558c45529af5398f32cae07195dbc63b --- /dev/null +++ b/skills/instruction-hierarchy-checks/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Instruction Hierarchy Checks" +short_description: "Work on instruction hierarchy checks for Prompting And Evaluation." +default_prompt: "Use this skill to help with instruction hierarchy checks in Prompting And Evaluation." diff --git a/skills/insurance-ai-workflows/SKILL.md b/skills/insurance-ai-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..57ceb425682a9bd97557f8e8128b7a740f43b71c --- /dev/null +++ b/skills/insurance-ai-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: insurance-ai-workflows +description: "Guidance for insurance AI workflows in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving insurance AI workflows, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Insurance AI Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for insurance AI workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on insurance AI workflows. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/insurance-ai-workflows/agents/openai.yaml b/skills/insurance-ai-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..2d5523ebd110a93c334704dd9b6cee2a8e8acb60 --- /dev/null +++ b/skills/insurance-ai-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Insurance AI Workflows" +short_description: "Work on insurance AI workflows for Domain AI." +default_prompt: "Use this skill to help with insurance AI workflows in Domain AI." diff --git a/skills/intent-detection/SKILL.md b/skills/intent-detection/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..c243cb6c01906c18cb0836db94fa0d2ec7645e74 --- /dev/null +++ b/skills/intent-detection/SKILL.md @@ -0,0 +1,29 @@ +--- +name: intent-detection +description: "Guidance for intent detection in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving intent detection, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Intent Detection + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for intent detection. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on intent detection. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/intent-detection/agents/openai.yaml b/skills/intent-detection/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..dacecc1e875c8caed0bbf84bb1913ab63d249f20 --- /dev/null +++ b/skills/intent-detection/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Intent Detection" +short_description: "Work on intent detection for Natural Language Processing." +default_prompt: "Use this skill to help with intent detection in Natural Language Processing." diff --git a/skills/internationalization/SKILL.md b/skills/internationalization/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..84550ad5c5469ee7ae07356205b0b9668664d059 --- /dev/null +++ b/skills/internationalization/SKILL.md @@ -0,0 +1,29 @@ +--- +name: internationalization +description: "Guidance for internationalization in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving internationalization, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Internationalization + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for internationalization. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on internationalization. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/internationalization/agents/openai.yaml b/skills/internationalization/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..5f380dddb4b0d25baf5e57f6874ae627694487c9 --- /dev/null +++ b/skills/internationalization/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Internationalization" +short_description: "Work on internationalization for Web Engineering." +default_prompt: "Use this skill to help with internationalization in Web Engineering." diff --git a/skills/ios-swift-apps/SKILL.md b/skills/ios-swift-apps/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..8544e27838b1d36054e57a9230e1a9e995aa9b69 --- /dev/null +++ b/skills/ios-swift-apps/SKILL.md @@ -0,0 +1,29 @@ +--- +name: ios-swift-apps +description: "Guidance for iOS Swift apps in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving iOS Swift apps, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# IOS Swift Apps + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for iOS Swift apps. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on iOS Swift apps. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/ios-swift-apps/agents/openai.yaml b/skills/ios-swift-apps/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7e8985c1ebb416cb1002a3634db7988ac10add26 --- /dev/null +++ b/skills/ios-swift-apps/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "IOS Swift Apps" +short_description: "Work on iOS Swift apps for Mobile App Engineering." +default_prompt: "Use this skill to help with iOS Swift apps in Mobile App Engineering." diff --git a/skills/iot-telemetry-ingestion/SKILL.md b/skills/iot-telemetry-ingestion/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..892cf9f5cd905a8d95a21896242032bb5251f867 --- /dev/null +++ b/skills/iot-telemetry-ingestion/SKILL.md @@ -0,0 +1,29 @@ +--- +name: iot-telemetry-ingestion +description: "Guidance for IoT telemetry ingestion in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving IoT telemetry ingestion, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# IOT Telemetry Ingestion + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for IoT telemetry ingestion. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on IoT telemetry ingestion. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/iot-telemetry-ingestion/agents/openai.yaml b/skills/iot-telemetry-ingestion/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..fb240109bf701d30d68897b6b1ce44a33156ba16 --- /dev/null +++ b/skills/iot-telemetry-ingestion/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "IOT Telemetry Ingestion" +short_description: "Work on IoT telemetry ingestion for Robotics And IoT." +default_prompt: "Use this skill to help with IoT telemetry ingestion in Robotics And IoT." diff --git a/skills/jwt-handling/SKILL.md b/skills/jwt-handling/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..2899e0b8fc3d158cda0f8985043121498a0cbdf2 --- /dev/null +++ b/skills/jwt-handling/SKILL.md @@ -0,0 +1,29 @@ +--- +name: jwt-handling +description: "Guidance for JWT handling in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving JWT handling, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# JWT Handling + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for JWT handling. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on JWT handling. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/jwt-handling/agents/openai.yaml b/skills/jwt-handling/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..8c06d9667d7d6be97e8be2cab56e2a160224b5a9 --- /dev/null +++ b/skills/jwt-handling/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "JWT Handling" +short_description: "Work on JWT handling for Security And Privacy." +default_prompt: "Use this skill to help with JWT handling in Security And Privacy." diff --git a/skills/key-rotation/SKILL.md b/skills/key-rotation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..e4251a636c344d4c0c80a97b177cb405ae456717 --- /dev/null +++ b/skills/key-rotation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: key-rotation +description: "Guidance for key rotation in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving key rotation, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# Key Rotation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for key rotation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on key rotation. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/key-rotation/agents/openai.yaml b/skills/key-rotation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..5edc224afc2d8f29e9158bba9ecddf21473b8261 --- /dev/null +++ b/skills/key-rotation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Key Rotation" +short_description: "Work on key rotation for Security And Privacy." +default_prompt: "Use this skill to help with key rotation in Security And Privacy." diff --git a/skills/keyword-extraction/SKILL.md b/skills/keyword-extraction/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..662d4eee5d21b1bf0ffaef8e1e84e1f21c643657 --- /dev/null +++ b/skills/keyword-extraction/SKILL.md @@ -0,0 +1,29 @@ +--- +name: keyword-extraction +description: "Guidance for keyword extraction in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving keyword extraction, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Keyword Extraction + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for keyword extraction. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on keyword extraction. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/keyword-extraction/agents/openai.yaml b/skills/keyword-extraction/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b24373170b18b859c5c59dc4f66acf787f79cf8e --- /dev/null +++ b/skills/keyword-extraction/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Keyword Extraction" +short_description: "Work on keyword extraction for Natural Language Processing." +default_prompt: "Use this skill to help with keyword extraction in Natural Language Processing." diff --git a/skills/knowledge-distillation/SKILL.md b/skills/knowledge-distillation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a55885c4ccf59b3fd358636ce5ad2c1eeba5008d --- /dev/null +++ b/skills/knowledge-distillation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: knowledge-distillation +description: "Guidance for knowledge distillation in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving knowledge distillation, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Knowledge Distillation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for knowledge distillation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on knowledge distillation. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/knowledge-distillation/agents/openai.yaml b/skills/knowledge-distillation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..1ec91773e76ed1be41bf781fad31687e0176be3c --- /dev/null +++ b/skills/knowledge-distillation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Knowledge Distillation" +short_description: "Work on knowledge distillation for Deep Learning." +default_prompt: "Use this skill to help with knowledge distillation in Deep Learning." diff --git a/skills/knowledge-graph-construction/SKILL.md b/skills/knowledge-graph-construction/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..2a352f650a161efffebdc65e4eed3b85e163cfdb --- /dev/null +++ b/skills/knowledge-graph-construction/SKILL.md @@ -0,0 +1,29 @@ +--- +name: knowledge-graph-construction +description: "Guidance for knowledge graph construction in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving knowledge graph construction, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Knowledge Graph Construction + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for knowledge graph construction. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on knowledge graph construction. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/knowledge-graph-construction/agents/openai.yaml b/skills/knowledge-graph-construction/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9de8c9fb0837ab23c7b7e8c656a6a15a27a95ead --- /dev/null +++ b/skills/knowledge-graph-construction/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Knowledge Graph Construction" +short_description: "Work on knowledge graph construction for Research And Scientific AI." +default_prompt: "Use this skill to help with knowledge graph construction in Research And Scientific AI." diff --git a/skills/knowledge-management-ai/SKILL.md b/skills/knowledge-management-ai/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..1d9102b729fb32ac1ba6786472718d17b7e214d0 --- /dev/null +++ b/skills/knowledge-management-ai/SKILL.md @@ -0,0 +1,29 @@ +--- +name: knowledge-management-ai +description: "Guidance for knowledge management AI in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving knowledge management AI, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Knowledge Management AI + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for knowledge management AI. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on knowledge management AI. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/knowledge-management-ai/agents/openai.yaml b/skills/knowledge-management-ai/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..8d425b6c8cf6a6c92d4df6a1df46165a0444a324 --- /dev/null +++ b/skills/knowledge-management-ai/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Knowledge Management AI" +short_description: "Work on knowledge management AI for Domain AI." +default_prompt: "Use this skill to help with knowledge management AI in Domain AI." diff --git a/skills/kubernetes-deployments/SKILL.md b/skills/kubernetes-deployments/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..c5d2dc561f6e44abf3f1cfef1154d336c34b3415 --- /dev/null +++ b/skills/kubernetes-deployments/SKILL.md @@ -0,0 +1,29 @@ +--- +name: kubernetes-deployments +description: "Guidance for Kubernetes deployments in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving Kubernetes deployments, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# Kubernetes Deployments + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for Kubernetes deployments. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on Kubernetes deployments. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/kubernetes-deployments/agents/openai.yaml b/skills/kubernetes-deployments/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9251c1036ea47e11ba0a3beec6335128d89b428f --- /dev/null +++ b/skills/kubernetes-deployments/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Kubernetes Deployments" +short_description: "Work on Kubernetes deployments for Cloud And DevOps." +default_prompt: "Use this skill to help with Kubernetes deployments in Cloud And DevOps." diff --git a/skills/lakehouse-architecture/SKILL.md b/skills/lakehouse-architecture/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..e62869a635a7678d9ebf505a95155ebeb7dc2609 --- /dev/null +++ b/skills/lakehouse-architecture/SKILL.md @@ -0,0 +1,29 @@ +--- +name: lakehouse-architecture +description: "Guidance for lakehouse architecture in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving lakehouse architecture, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Lakehouse Architecture + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for lakehouse architecture. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on lakehouse architecture. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/lakehouse-architecture/agents/openai.yaml b/skills/lakehouse-architecture/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..2400004e069297f224889f346c3c27fdaae60aa5 --- /dev/null +++ b/skills/lakehouse-architecture/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Lakehouse Architecture" +short_description: "Work on lakehouse architecture for Data Engineering." +default_prompt: "Use this skill to help with lakehouse architecture in Data Engineering." diff --git a/skills/language-detection/SKILL.md b/skills/language-detection/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..9df989bc2b32797c17f5647b0daef380a1cb16b4 --- /dev/null +++ b/skills/language-detection/SKILL.md @@ -0,0 +1,29 @@ +--- +name: language-detection +description: "Guidance for language detection in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving language detection, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Language Detection + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for language detection. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on language detection. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/language-detection/agents/openai.yaml b/skills/language-detection/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..8beb5fc3a7a8818b577b70f4100db70cffd1f5b1 --- /dev/null +++ b/skills/language-detection/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Language Detection" +short_description: "Work on language detection for Natural Language Processing." +default_prompt: "Use this skill to help with language detection in Natural Language Processing." diff --git a/skills/layout-aware-extraction/SKILL.md b/skills/layout-aware-extraction/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..63af1d5fd0270cfc1cbb6e5d3f90e312273d400e --- /dev/null +++ b/skills/layout-aware-extraction/SKILL.md @@ -0,0 +1,29 @@ +--- +name: layout-aware-extraction +description: "Guidance for layout aware extraction in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving layout aware extraction, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Layout Aware Extraction + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for layout aware extraction. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on layout aware extraction. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/layout-aware-extraction/agents/openai.yaml b/skills/layout-aware-extraction/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e11fa2c0bb7bee5ae18151c06f6173e36b81d81d --- /dev/null +++ b/skills/layout-aware-extraction/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Layout Aware Extraction" +short_description: "Work on layout aware extraction for Multimodal AI." +default_prompt: "Use this skill to help with layout aware extraction in Multimodal AI." diff --git a/skills/learning-rate-schedules/SKILL.md b/skills/learning-rate-schedules/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..b9de5e02672f0577c1a5fa603033cf26af7f633d --- /dev/null +++ b/skills/learning-rate-schedules/SKILL.md @@ -0,0 +1,29 @@ +--- +name: learning-rate-schedules +description: "Guidance for learning rate schedules in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving learning rate schedules, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Learning Rate Schedules + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for learning rate schedules. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on learning rate schedules. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/learning-rate-schedules/agents/openai.yaml b/skills/learning-rate-schedules/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9cde0134a20c67f8a763f15a3f98d7722089925a --- /dev/null +++ b/skills/learning-rate-schedules/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Learning Rate Schedules" +short_description: "Work on learning rate schedules for Deep Learning." +default_prompt: "Use this skill to help with learning rate schedules in Deep Learning." diff --git a/skills/legal-ai-workflows/SKILL.md b/skills/legal-ai-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..2cf5a1a611cb7ff2e4c1d3f8fcd58f472d76ecc7 --- /dev/null +++ b/skills/legal-ai-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: legal-ai-workflows +description: "Guidance for legal AI workflows in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving legal AI workflows, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Legal AI Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for legal AI workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on legal AI workflows. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/legal-ai-workflows/agents/openai.yaml b/skills/legal-ai-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..5bc77a97d9e6d158603c358608920447b01c4028 --- /dev/null +++ b/skills/legal-ai-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Legal AI Workflows" +short_description: "Work on legal AI workflows for Domain AI." +default_prompt: "Use this skill to help with legal AI workflows in Domain AI." diff --git a/skills/legal-document-nlp/SKILL.md b/skills/legal-document-nlp/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..e6829c37c5ca5f7af58d5f98bdffccaae2f125bd --- /dev/null +++ b/skills/legal-document-nlp/SKILL.md @@ -0,0 +1,29 @@ +--- +name: legal-document-nlp +description: "Guidance for legal document NLP in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving legal document NLP, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Legal Document NLP + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for legal document NLP. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on legal document NLP. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/legal-document-nlp/agents/openai.yaml b/skills/legal-document-nlp/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..92559a234c946fcca30ed75f41a07ca1665d04c1 --- /dev/null +++ b/skills/legal-document-nlp/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Legal Document NLP" +short_description: "Work on legal document NLP for Natural Language Processing." +default_prompt: "Use this skill to help with legal document NLP in Natural Language Processing." diff --git a/skills/literature-review-automation/SKILL.md b/skills/literature-review-automation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..2e6e3c417d47bacca8635f1730bc80fc8c924e99 --- /dev/null +++ b/skills/literature-review-automation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: literature-review-automation +description: "Guidance for literature review automation in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving literature review automation, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Literature Review Automation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for literature review automation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on literature review automation. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/literature-review-automation/agents/openai.yaml b/skills/literature-review-automation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..8d96fd27f933c4c51408c0ece214ec7f694fabdb --- /dev/null +++ b/skills/literature-review-automation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Literature Review Automation" +short_description: "Work on literature review automation for Research And Scientific AI." +default_prompt: "Use this skill to help with literature review automation in Research And Scientific AI." diff --git a/skills/llm-judge-calibration/SKILL.md b/skills/llm-judge-calibration/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a365fc2fd018bc2262b733394bdc402a3144f96f --- /dev/null +++ b/skills/llm-judge-calibration/SKILL.md @@ -0,0 +1,29 @@ +--- +name: llm-judge-calibration +description: "Guidance for LLM judge calibration in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving LLM judge calibration, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# LLM Judge Calibration + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for LLM judge calibration. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on LLM judge calibration. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/llm-judge-calibration/agents/openai.yaml b/skills/llm-judge-calibration/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..af4868f84ae7ae029b474e08e495e2e5c9bc2964 --- /dev/null +++ b/skills/llm-judge-calibration/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "LLM Judge Calibration" +short_description: "Work on LLM judge calibration for Prompting And Evaluation." +default_prompt: "Use this skill to help with LLM judge calibration in Prompting And Evaluation." diff --git a/skills/llm-observability/SKILL.md b/skills/llm-observability/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..340249d4e461072499125bbf5d1de12b9b6aca8b --- /dev/null +++ b/skills/llm-observability/SKILL.md @@ -0,0 +1,29 @@ +--- +name: llm-observability +description: "Guidance for LLM observability in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving LLM observability, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# LLM Observability + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for LLM observability. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on LLM observability. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/llm-observability/agents/openai.yaml b/skills/llm-observability/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..984f6a8a1867e3edce35f8510fa70cbd92d52d3d --- /dev/null +++ b/skills/llm-observability/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "LLM Observability" +short_description: "Work on LLM observability for LLM Engineering." +default_prompt: "Use this skill to help with LLM observability in LLM Engineering." diff --git a/skills/load-balancer-setup/SKILL.md b/skills/load-balancer-setup/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..5970263c271c535e84223b0ee3bccdd50317bc29 --- /dev/null +++ b/skills/load-balancer-setup/SKILL.md @@ -0,0 +1,29 @@ +--- +name: load-balancer-setup +description: "Guidance for load balancer setup in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving load balancer setup, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# Load Balancer Setup + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for load balancer setup. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on load balancer setup. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/load-balancer-setup/agents/openai.yaml b/skills/load-balancer-setup/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d7913781aa03a4b235fb45232db4a0b78d75c2da --- /dev/null +++ b/skills/load-balancer-setup/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Load Balancer Setup" +short_description: "Work on load balancer setup for Cloud And DevOps." +default_prompt: "Use this skill to help with load balancer setup in Cloud And DevOps." diff --git a/skills/location-features/SKILL.md b/skills/location-features/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..65634f405f30bbfac306a5618a52b6d9ccb8d140 --- /dev/null +++ b/skills/location-features/SKILL.md @@ -0,0 +1,29 @@ +--- +name: location-features +description: "Guidance for location features in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving location features, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Location Features + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for location features. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on location features. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/location-features/agents/openai.yaml b/skills/location-features/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..1450c5319bdc7a36f953569f05c1499ed617f52f --- /dev/null +++ b/skills/location-features/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Location Features" +short_description: "Work on location features for Mobile App Engineering." +default_prompt: "Use this skill to help with location features in Mobile App Engineering." diff --git a/skills/log-analytics-pipelines/SKILL.md b/skills/log-analytics-pipelines/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..86881b0855cd9903bed03ea12f9a6d2e4f3e9962 --- /dev/null +++ b/skills/log-analytics-pipelines/SKILL.md @@ -0,0 +1,29 @@ +--- +name: log-analytics-pipelines +description: "Guidance for log analytics pipelines in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving log analytics pipelines, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Log Analytics Pipelines + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for log analytics pipelines. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on log analytics pipelines. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/log-analytics-pipelines/agents/openai.yaml b/skills/log-analytics-pipelines/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..c6b1da0a738c33c0bd56026f889d8c929b6bf594 --- /dev/null +++ b/skills/log-analytics-pipelines/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Log Analytics Pipelines" +short_description: "Work on log analytics pipelines for Data Engineering." +default_prompt: "Use this skill to help with log analytics pipelines in Data Engineering." diff --git a/skills/logging-pipelines/SKILL.md b/skills/logging-pipelines/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..ef0a60ef4ee8e45f9e6842bf18c107fb186f8e09 --- /dev/null +++ b/skills/logging-pipelines/SKILL.md @@ -0,0 +1,29 @@ +--- +name: logging-pipelines +description: "Guidance for logging pipelines in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving logging pipelines, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# Logging Pipelines + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for logging pipelines. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on logging pipelines. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/logging-pipelines/agents/openai.yaml b/skills/logging-pipelines/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..607e9c63373161b3a022970c2eff0e6e897e411d --- /dev/null +++ b/skills/logging-pipelines/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Logging Pipelines" +short_description: "Work on logging pipelines for Cloud And DevOps." +default_prompt: "Use this skill to help with logging pipelines in Cloud And DevOps." diff --git a/skills/logistics-ai-workflows/SKILL.md b/skills/logistics-ai-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..d99da03b4d2f74b916db5934abb7ac21b951a147 --- /dev/null +++ b/skills/logistics-ai-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: logistics-ai-workflows +description: "Guidance for logistics AI workflows in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving logistics AI workflows, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Logistics AI Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for logistics AI workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on logistics AI workflows. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/logistics-ai-workflows/agents/openai.yaml b/skills/logistics-ai-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..22155186cf3c1840e955000a3c84d4b2ceb3382e --- /dev/null +++ b/skills/logistics-ai-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Logistics AI Workflows" +short_description: "Work on logistics AI workflows for Domain AI." +default_prompt: "Use this skill to help with logistics AI workflows in Domain AI." diff --git a/skills/long-context-workflows/SKILL.md b/skills/long-context-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..07359188eafacc7c50d770741fb8a9749399707a --- /dev/null +++ b/skills/long-context-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: long-context-workflows +description: "Guidance for long context workflows in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving long context workflows, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Long Context Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for long context workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on long context workflows. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/long-context-workflows/agents/openai.yaml b/skills/long-context-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7eae187c7444bcfd73ea9a2f26297712ed927941 --- /dev/null +++ b/skills/long-context-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Long Context Workflows" +short_description: "Work on long context workflows for LLM Engineering." +default_prompt: "Use this skill to help with long context workflows in LLM Engineering." diff --git a/skills/loss-function-design/SKILL.md b/skills/loss-function-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a468167638137a930c932087645a368e1c5a06c7 --- /dev/null +++ b/skills/loss-function-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: loss-function-design +description: "Guidance for loss function design in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving loss function design, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Loss Function Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for loss function design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on loss function design. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/loss-function-design/agents/openai.yaml b/skills/loss-function-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ddec563cb6cf27d654a078653c123f8028fbb8b8 --- /dev/null +++ b/skills/loss-function-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Loss Function Design" +short_description: "Work on loss function design for Deep Learning." +default_prompt: "Use this skill to help with loss function design in Deep Learning." diff --git a/skills/low-latency-streaming-asr/SKILL.md b/skills/low-latency-streaming-asr/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..ba3fcfa80a4323bec69224ae19835839b22436ca --- /dev/null +++ b/skills/low-latency-streaming-asr/SKILL.md @@ -0,0 +1,29 @@ +--- +name: low-latency-streaming-asr +description: "Guidance for low latency streaming ASR in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving low latency streaming ASR, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Low Latency Streaming ASR + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for low latency streaming ASR. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on low latency streaming ASR. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/low-latency-streaming-asr/agents/openai.yaml b/skills/low-latency-streaming-asr/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..0bb12fa820d2fc8973603559735485fdf913a115 --- /dev/null +++ b/skills/low-latency-streaming-asr/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Low Latency Streaming ASR" +short_description: "Work on low latency streaming ASR for Speech And Audio." +default_prompt: "Use this skill to help with low latency streaming ASR in Speech And Audio." diff --git a/skills/low-power-ml/SKILL.md b/skills/low-power-ml/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..56aea1378d8efb2b0396a45eb991318eafd91dfe --- /dev/null +++ b/skills/low-power-ml/SKILL.md @@ -0,0 +1,29 @@ +--- +name: low-power-ml +description: "Guidance for low power ML in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving low power ML, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# Low Power ML + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for low power ML. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on low power ML. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/low-power-ml/agents/openai.yaml b/skills/low-power-ml/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..8f1e2251cb210d616dc7a3b6d74974b263611449 --- /dev/null +++ b/skills/low-power-ml/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Low Power ML" +short_description: "Work on low power ML for Robotics And IoT." +default_prompt: "Use this skill to help with low power ML in Robotics And IoT." diff --git a/skills/machine-translation/SKILL.md b/skills/machine-translation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..67a30e6927071d12d8026bfedb6de0646b83cb00 --- /dev/null +++ b/skills/machine-translation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: machine-translation +description: "Guidance for machine translation in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving machine translation, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Machine Translation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for machine translation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on machine translation. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/machine-translation/agents/openai.yaml b/skills/machine-translation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ec2daaa5fd4c86057964b54f1477ff15895db835 --- /dev/null +++ b/skills/machine-translation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Machine Translation" +short_description: "Work on machine translation for Natural Language Processing." +default_prompt: "Use this skill to help with machine translation in Natural Language Processing." diff --git a/skills/manufacturing-ai-workflows/SKILL.md b/skills/manufacturing-ai-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..9ca3da605388f3e6fb83261a9c1987bd10c33392 --- /dev/null +++ b/skills/manufacturing-ai-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: manufacturing-ai-workflows +description: "Guidance for manufacturing AI workflows in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving manufacturing AI workflows, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Manufacturing AI Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for manufacturing AI workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on manufacturing AI workflows. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/manufacturing-ai-workflows/agents/openai.yaml b/skills/manufacturing-ai-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..a2ab25a787923998625da3d88dadfafa04ed8b14 --- /dev/null +++ b/skills/manufacturing-ai-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Manufacturing AI Workflows" +short_description: "Work on manufacturing AI workflows for Domain AI." +default_prompt: "Use this skill to help with manufacturing AI workflows in Domain AI." diff --git a/skills/marketing-ai-workflows/SKILL.md b/skills/marketing-ai-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a098a1c8d1de3d98d8756e9393ad07e1bbd98f3f --- /dev/null +++ b/skills/marketing-ai-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: marketing-ai-workflows +description: "Guidance for marketing AI workflows in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving marketing AI workflows, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Marketing AI Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for marketing AI workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on marketing AI workflows. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/marketing-ai-workflows/agents/openai.yaml b/skills/marketing-ai-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ea1c1e9eeb075371b76ed0534877e4c793502f39 --- /dev/null +++ b/skills/marketing-ai-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Marketing AI Workflows" +short_description: "Work on marketing AI workflows for Domain AI." +default_prompt: "Use this skill to help with marketing AI workflows in Domain AI." diff --git a/skills/materials-discovery-ml/SKILL.md b/skills/materials-discovery-ml/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..6c820b124cbad025ffd6ef6f404b29ae7fa1786c --- /dev/null +++ b/skills/materials-discovery-ml/SKILL.md @@ -0,0 +1,29 @@ +--- +name: materials-discovery-ml +description: "Guidance for materials discovery ML in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving materials discovery ML, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Materials Discovery ML + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for materials discovery ML. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on materials discovery ML. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/materials-discovery-ml/agents/openai.yaml b/skills/materials-discovery-ml/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..66a400328a930f3e68ab757e0e008969046e5a5a --- /dev/null +++ b/skills/materials-discovery-ml/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Materials Discovery ML" +short_description: "Work on materials discovery ML for Research And Scientific AI." +default_prompt: "Use this skill to help with materials discovery ML in Research And Scientific AI." diff --git a/skills/media-ai-workflows/SKILL.md b/skills/media-ai-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..8140d11cd6577bfb28104c0de2ecacee9d8828a4 --- /dev/null +++ b/skills/media-ai-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: media-ai-workflows +description: "Guidance for media AI workflows in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving media AI workflows, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Media AI Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for media AI workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on media AI workflows. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/media-ai-workflows/agents/openai.yaml b/skills/media-ai-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..0968a0310c06e397b6fbb1648cc63bcf7ca21286 --- /dev/null +++ b/skills/media-ai-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Media AI Workflows" +short_description: "Work on media AI workflows for Domain AI." +default_prompt: "Use this skill to help with media AI workflows in Domain AI." diff --git a/skills/medical-imaging/SKILL.md b/skills/medical-imaging/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..214082d47ad1c4504c72b3292c4c05c9dae50879 --- /dev/null +++ b/skills/medical-imaging/SKILL.md @@ -0,0 +1,29 @@ +--- +name: medical-imaging +description: "Guidance for medical imaging in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving medical imaging, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Medical Imaging + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for medical imaging. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on medical imaging. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/medical-imaging/agents/openai.yaml b/skills/medical-imaging/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..8aa9659091ced7f6fbdf1bb440b113a2e3ac1f77 --- /dev/null +++ b/skills/medical-imaging/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Medical Imaging" +short_description: "Work on medical imaging for Computer Vision." +default_prompt: "Use this skill to help with medical imaging in Computer Vision." diff --git a/skills/medical-multimodal-analysis/SKILL.md b/skills/medical-multimodal-analysis/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..3e3fac3c6c170b636a51ad955a312f0dd5e73e50 --- /dev/null +++ b/skills/medical-multimodal-analysis/SKILL.md @@ -0,0 +1,29 @@ +--- +name: medical-multimodal-analysis +description: "Guidance for medical multimodal analysis in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving medical multimodal analysis, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Medical Multimodal Analysis + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for medical multimodal analysis. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on medical multimodal analysis. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/medical-multimodal-analysis/agents/openai.yaml b/skills/medical-multimodal-analysis/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..0f09aaf96927fd79800637ff9719f9076c325c49 --- /dev/null +++ b/skills/medical-multimodal-analysis/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Medical Multimodal Analysis" +short_description: "Work on medical multimodal analysis for Multimodal AI." +default_prompt: "Use this skill to help with medical multimodal analysis in Multimodal AI." diff --git a/skills/metric-learning/SKILL.md b/skills/metric-learning/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..0415b66b7627ad17b99896f5b4d5c08fb3ebe39d --- /dev/null +++ b/skills/metric-learning/SKILL.md @@ -0,0 +1,29 @@ +--- +name: metric-learning +description: "Guidance for metric learning in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving metric learning, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Metric Learning + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for metric learning. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on metric learning. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/metric-learning/agents/openai.yaml b/skills/metric-learning/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..0725c6dda878dcb0753214ad7a08cbf7e7c0aca3 --- /dev/null +++ b/skills/metric-learning/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Metric Learning" +short_description: "Work on metric learning for Deep Learning." +default_prompt: "Use this skill to help with metric learning in Deep Learning." diff --git a/skills/metrics-alerts/SKILL.md b/skills/metrics-alerts/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..b3b89f6dd771957e6e664b236ddadb2aa3a608a1 --- /dev/null +++ b/skills/metrics-alerts/SKILL.md @@ -0,0 +1,29 @@ +--- +name: metrics-alerts +description: "Guidance for metrics alerts in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving metrics alerts, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# Metrics Alerts + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for metrics alerts. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on metrics alerts. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/metrics-alerts/agents/openai.yaml b/skills/metrics-alerts/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ed99aaabd2b09627dc01d5b964744dea78f0d649 --- /dev/null +++ b/skills/metrics-alerts/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Metrics Alerts" +short_description: "Work on metrics alerts for Cloud And DevOps." +default_prompt: "Use this skill to help with metrics alerts in Cloud And DevOps." diff --git a/skills/metrics-layer-design/SKILL.md b/skills/metrics-layer-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..3924b8276142e04668ee60f3786db5391dd252f6 --- /dev/null +++ b/skills/metrics-layer-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: metrics-layer-design +description: "Guidance for metrics layer design in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving metrics layer design, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Metrics Layer Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for metrics layer design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on metrics layer design. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/metrics-layer-design/agents/openai.yaml b/skills/metrics-layer-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d4216d4741a377171dccedcbb684f805b1750a3b --- /dev/null +++ b/skills/metrics-layer-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Metrics Layer Design" +short_description: "Work on metrics layer design for Data Engineering." +default_prompt: "Use this skill to help with metrics layer design in Data Engineering." diff --git a/skills/microcontroller-inference/SKILL.md b/skills/microcontroller-inference/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..2809c921ba39b85b8df962336bfaa438cae93484 --- /dev/null +++ b/skills/microcontroller-inference/SKILL.md @@ -0,0 +1,29 @@ +--- +name: microcontroller-inference +description: "Guidance for microcontroller inference in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving microcontroller inference, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# Microcontroller Inference + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for microcontroller inference. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on microcontroller inference. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/microcontroller-inference/agents/openai.yaml b/skills/microcontroller-inference/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3331fc26ca3bb21f381e044a4149045f47bbcaed --- /dev/null +++ b/skills/microcontroller-inference/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Microcontroller Inference" +short_description: "Work on microcontroller inference for Robotics And IoT." +default_prompt: "Use this skill to help with microcontroller inference in Robotics And IoT." diff --git a/skills/migration-planning/SKILL.md b/skills/migration-planning/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..1b4262a1dd66a94b917ef23f953280a6dc37236d --- /dev/null +++ b/skills/migration-planning/SKILL.md @@ -0,0 +1,29 @@ +--- +name: migration-planning +description: "Guidance for migration planning in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving migration planning, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# Migration Planning + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for migration planning. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on migration planning. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/migration-planning/agents/openai.yaml b/skills/migration-planning/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..dc1aceb9f992f920748766a5f623ffe1b477fc8e --- /dev/null +++ b/skills/migration-planning/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Migration Planning" +short_description: "Work on migration planning for Databases And Analytics." +default_prompt: "Use this skill to help with migration planning in Databases And Analytics." diff --git a/skills/mixed-precision-training/SKILL.md b/skills/mixed-precision-training/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..32ec10d70edae0566f95345c8f7aa5ff66ca1a3f --- /dev/null +++ b/skills/mixed-precision-training/SKILL.md @@ -0,0 +1,29 @@ +--- +name: mixed-precision-training +description: "Guidance for mixed precision training in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving mixed precision training, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Mixed Precision Training + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for mixed precision training. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on mixed precision training. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/mixed-precision-training/agents/openai.yaml b/skills/mixed-precision-training/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..868090ccf5cf10fcdca9e42b5f974488fe30c0de --- /dev/null +++ b/skills/mixed-precision-training/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Mixed Precision Training" +short_description: "Work on mixed precision training for Deep Learning." +default_prompt: "Use this skill to help with mixed precision training in Deep Learning." diff --git a/skills/mobile-accessibility/SKILL.md b/skills/mobile-accessibility/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..98f270681c0cd7cfd3d7a30d7027048132d8b1e3 --- /dev/null +++ b/skills/mobile-accessibility/SKILL.md @@ -0,0 +1,29 @@ +--- +name: mobile-accessibility +description: "Guidance for mobile accessibility in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving mobile accessibility, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Mobile Accessibility + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for mobile accessibility. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on mobile accessibility. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/mobile-accessibility/agents/openai.yaml b/skills/mobile-accessibility/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..0c84acc8b32ec612d6f2bf29fdfebaa4ff4faeb0 --- /dev/null +++ b/skills/mobile-accessibility/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Mobile Accessibility" +short_description: "Work on mobile accessibility for Mobile App Engineering." +default_prompt: "Use this skill to help with mobile accessibility in Mobile App Engineering." diff --git a/skills/mobile-analytics/SKILL.md b/skills/mobile-analytics/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..2ee22e244251e6a8db43df71719f829676ce878b --- /dev/null +++ b/skills/mobile-analytics/SKILL.md @@ -0,0 +1,29 @@ +--- +name: mobile-analytics +description: "Guidance for mobile analytics in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving mobile analytics, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Mobile Analytics + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for mobile analytics. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on mobile analytics. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/mobile-analytics/agents/openai.yaml b/skills/mobile-analytics/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..587e390b73b12a4395ed337b9dabe02edbde9d47 --- /dev/null +++ b/skills/mobile-analytics/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Mobile Analytics" +short_description: "Work on mobile analytics for Mobile App Engineering." +default_prompt: "Use this skill to help with mobile analytics in Mobile App Engineering." diff --git a/skills/mobile-authentication/SKILL.md b/skills/mobile-authentication/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..6b8c4ef914e653f95f058d81c63db0490a5198f1 --- /dev/null +++ b/skills/mobile-authentication/SKILL.md @@ -0,0 +1,29 @@ +--- +name: mobile-authentication +description: "Guidance for mobile authentication in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving mobile authentication, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Mobile Authentication + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for mobile authentication. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on mobile authentication. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/mobile-authentication/agents/openai.yaml b/skills/mobile-authentication/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b58342ab43bf0f20d0a80bd3afb4584d1bf832c2 --- /dev/null +++ b/skills/mobile-authentication/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Mobile Authentication" +short_description: "Work on mobile authentication for Mobile App Engineering." +default_prompt: "Use this skill to help with mobile authentication in Mobile App Engineering." diff --git a/skills/mobile-navigation/SKILL.md b/skills/mobile-navigation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..151166a34aca011e482ef1c3450ccfb73d409571 --- /dev/null +++ b/skills/mobile-navigation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: mobile-navigation +description: "Guidance for mobile navigation in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving mobile navigation, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Mobile Navigation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for mobile navigation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on mobile navigation. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/mobile-navigation/agents/openai.yaml b/skills/mobile-navigation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..0d157e9103a677458cec15612e7d33cdaf8d0947 --- /dev/null +++ b/skills/mobile-navigation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Mobile Navigation" +short_description: "Work on mobile navigation for Mobile App Engineering." +default_prompt: "Use this skill to help with mobile navigation in Mobile App Engineering." diff --git a/skills/mobile-onboarding/SKILL.md b/skills/mobile-onboarding/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..016d94d97f33ee8630c189a1f12f8db13a683590 --- /dev/null +++ b/skills/mobile-onboarding/SKILL.md @@ -0,0 +1,29 @@ +--- +name: mobile-onboarding +description: "Guidance for mobile onboarding in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving mobile onboarding, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Mobile Onboarding + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for mobile onboarding. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on mobile onboarding. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/mobile-onboarding/agents/openai.yaml b/skills/mobile-onboarding/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..df51cef7128ff9be1741c34ad8b564d15a1108de --- /dev/null +++ b/skills/mobile-onboarding/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Mobile Onboarding" +short_description: "Work on mobile onboarding for Mobile App Engineering." +default_prompt: "Use this skill to help with mobile onboarding in Mobile App Engineering." diff --git a/skills/mobile-performance/SKILL.md b/skills/mobile-performance/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..41bbd9db8583fdfec7186e5c593089194b6f9bd1 --- /dev/null +++ b/skills/mobile-performance/SKILL.md @@ -0,0 +1,29 @@ +--- +name: mobile-performance +description: "Guidance for mobile performance in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving mobile performance, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Mobile Performance + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for mobile performance. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on mobile performance. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/mobile-performance/agents/openai.yaml b/skills/mobile-performance/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ba941d604ce535f0d49ad17cb53b228c524106ac --- /dev/null +++ b/skills/mobile-performance/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Mobile Performance" +short_description: "Work on mobile performance for Mobile App Engineering." +default_prompt: "Use this skill to help with mobile performance in Mobile App Engineering." diff --git a/skills/mobile-release-pipelines/SKILL.md b/skills/mobile-release-pipelines/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..08ccad39ae48d6c7078d7870ab5d09845be37d2e --- /dev/null +++ b/skills/mobile-release-pipelines/SKILL.md @@ -0,0 +1,29 @@ +--- +name: mobile-release-pipelines +description: "Guidance for mobile release pipelines in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving mobile release pipelines, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Mobile Release Pipelines + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for mobile release pipelines. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on mobile release pipelines. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/mobile-release-pipelines/agents/openai.yaml b/skills/mobile-release-pipelines/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..a21ed517308e5970690ec028ba4decb5f12ae0a4 --- /dev/null +++ b/skills/mobile-release-pipelines/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Mobile Release Pipelines" +short_description: "Work on mobile release pipelines for Mobile App Engineering." +default_prompt: "Use this skill to help with mobile release pipelines in Mobile App Engineering." diff --git a/skills/mobile-test-automation/SKILL.md b/skills/mobile-test-automation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..8bbf84c9b5bb992041fe8eeae9eb4143aaca6a96 --- /dev/null +++ b/skills/mobile-test-automation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: mobile-test-automation +description: "Guidance for mobile test automation in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving mobile test automation, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Mobile Test Automation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for mobile test automation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on mobile test automation. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/mobile-test-automation/agents/openai.yaml b/skills/mobile-test-automation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b17c1feb73986b4fcb1b9253da5421bf3869f965 --- /dev/null +++ b/skills/mobile-test-automation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Mobile Test Automation" +short_description: "Work on mobile test automation for Mobile App Engineering." +default_prompt: "Use this skill to help with mobile test automation in Mobile App Engineering." diff --git a/skills/model-calibration/SKILL.md b/skills/model-calibration/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..53009fde0d1e2159d0e264db3ae0cc23fc71a828 --- /dev/null +++ b/skills/model-calibration/SKILL.md @@ -0,0 +1,29 @@ +--- +name: model-calibration +description: "Guidance for model calibration in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving model calibration, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Model Calibration + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for model calibration. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on model calibration. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/model-calibration/agents/openai.yaml b/skills/model-calibration/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e8726f055a4c5950d49974abb86c5a255e8f50d5 --- /dev/null +++ b/skills/model-calibration/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Model Calibration" +short_description: "Work on model calibration for Machine Learning." +default_prompt: "Use this skill to help with model calibration in Machine Learning." diff --git a/skills/model-cards/SKILL.md b/skills/model-cards/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..8bd44c0162c597b9f147db49bfb7ad9d7204268a --- /dev/null +++ b/skills/model-cards/SKILL.md @@ -0,0 +1,29 @@ +--- +name: model-cards +description: "Guidance for model cards in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving model cards, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# Model Cards + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for model cards. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on model cards. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/model-cards/agents/openai.yaml b/skills/model-cards/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..2385604197acffd548f075c2a5b3696b07d497d4 --- /dev/null +++ b/skills/model-cards/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Model Cards" +short_description: "Work on model cards for MLOps." +default_prompt: "Use this skill to help with model cards in MLOps." diff --git a/skills/model-choice-ux/SKILL.md b/skills/model-choice-ux/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..cab03f348d26047f608c51f00420f7722b4fd1d3 --- /dev/null +++ b/skills/model-choice-ux/SKILL.md @@ -0,0 +1,29 @@ +--- +name: model-choice-ux +description: "Guidance for model choice UX in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving model choice UX, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# Model Choice UX + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for model choice UX. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on model choice UX. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/model-choice-ux/agents/openai.yaml b/skills/model-choice-ux/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..33f6ab366042ed6fcbeb03d33d54fecdcc7d5777 --- /dev/null +++ b/skills/model-choice-ux/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Model Choice UX" +short_description: "Work on model choice UX for AI Product And UX." +default_prompt: "Use this skill to help with model choice UX in AI Product And UX." diff --git a/skills/model-explainability/SKILL.md b/skills/model-explainability/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..7d8e3e1150b25eb8c21268027733861dfe22669a --- /dev/null +++ b/skills/model-explainability/SKILL.md @@ -0,0 +1,29 @@ +--- +name: model-explainability +description: "Guidance for model explainability in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving model explainability, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Model Explainability + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for model explainability. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on model explainability. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/model-explainability/agents/openai.yaml b/skills/model-explainability/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..8a3c122c75064c5b807a9476f9f25e6356299897 --- /dev/null +++ b/skills/model-explainability/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Model Explainability" +short_description: "Work on model explainability for Machine Learning." +default_prompt: "Use this skill to help with model explainability in Machine Learning." diff --git a/skills/model-fallback-strategy/SKILL.md b/skills/model-fallback-strategy/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..2eab75c70e9cb5774108db09f039e56afd5fdf8c --- /dev/null +++ b/skills/model-fallback-strategy/SKILL.md @@ -0,0 +1,29 @@ +--- +name: model-fallback-strategy +description: "Guidance for model fallback strategy in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving model fallback strategy, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Model Fallback Strategy + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for model fallback strategy. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on model fallback strategy. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/model-fallback-strategy/agents/openai.yaml b/skills/model-fallback-strategy/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..6d458bd53fbb1661ac3a2f820eecc1ee9ef045da --- /dev/null +++ b/skills/model-fallback-strategy/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Model Fallback Strategy" +short_description: "Work on model fallback strategy for LLM Engineering." +default_prompt: "Use this skill to help with model fallback strategy in LLM Engineering." diff --git a/skills/model-monitoring/SKILL.md b/skills/model-monitoring/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..91056980373329ef8aacba62a5584a0a8062fa72 --- /dev/null +++ b/skills/model-monitoring/SKILL.md @@ -0,0 +1,29 @@ +--- +name: model-monitoring +description: "Guidance for model monitoring in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving model monitoring, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# Model Monitoring + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for model monitoring. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on model monitoring. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/model-monitoring/agents/openai.yaml b/skills/model-monitoring/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..fe19e6b9dc3047d7095cee58f7777eee1a56b926 --- /dev/null +++ b/skills/model-monitoring/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Model Monitoring" +short_description: "Work on model monitoring for MLOps." +default_prompt: "Use this skill to help with model monitoring in MLOps." diff --git a/skills/model-pruning/SKILL.md b/skills/model-pruning/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..8c2595e47f93e37e47c6003cc35c731bc21a236c --- /dev/null +++ b/skills/model-pruning/SKILL.md @@ -0,0 +1,29 @@ +--- +name: model-pruning +description: "Guidance for model pruning in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving model pruning, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Model Pruning + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for model pruning. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on model pruning. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/model-pruning/agents/openai.yaml b/skills/model-pruning/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..efae6a1b46d2066fbd840313205294c36ed3bdf8 --- /dev/null +++ b/skills/model-pruning/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Model Pruning" +short_description: "Work on model pruning for Deep Learning." +default_prompt: "Use this skill to help with model pruning in Deep Learning." diff --git a/skills/model-quantization/SKILL.md b/skills/model-quantization/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..131d8506345b77c590577966fa1d1843e2763e59 --- /dev/null +++ b/skills/model-quantization/SKILL.md @@ -0,0 +1,29 @@ +--- +name: model-quantization +description: "Guidance for model quantization in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving model quantization, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Model Quantization + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for model quantization. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on model quantization. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/model-quantization/agents/openai.yaml b/skills/model-quantization/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e0f1d89c0f2b3d12e6a29414c7d9f898c67083ef --- /dev/null +++ b/skills/model-quantization/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Model Quantization" +short_description: "Work on model quantization for Deep Learning." +default_prompt: "Use this skill to help with model quantization in Deep Learning." diff --git a/skills/model-registry-design/SKILL.md b/skills/model-registry-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..c436b5a5d7682e8ac9c1bd739c3f62a5e83f505b --- /dev/null +++ b/skills/model-registry-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: model-registry-design +description: "Guidance for model registry design in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving model registry design, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# Model Registry Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for model registry design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on model registry design. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/model-registry-design/agents/openai.yaml b/skills/model-registry-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..cb2a73203858a2f8e9660ec54375f01f5828dc55 --- /dev/null +++ b/skills/model-registry-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Model Registry Design" +short_description: "Work on model registry design for MLOps." +default_prompt: "Use this skill to help with model registry design in MLOps." diff --git a/skills/model-selection-benchmarking/SKILL.md b/skills/model-selection-benchmarking/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a7bc3fa19bfdee1d71ab9560ed6d3cc3fafc17d5 --- /dev/null +++ b/skills/model-selection-benchmarking/SKILL.md @@ -0,0 +1,29 @@ +--- +name: model-selection-benchmarking +description: "Guidance for model selection benchmarking in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving model selection benchmarking, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Model Selection Benchmarking + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for model selection benchmarking. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on model selection benchmarking. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/model-selection-benchmarking/agents/openai.yaml b/skills/model-selection-benchmarking/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..1b4d730a7c0b3735dae4989eeaaf300284e8d515 --- /dev/null +++ b/skills/model-selection-benchmarking/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Model Selection Benchmarking" +short_description: "Work on model selection benchmarking for LLM Engineering." +default_prompt: "Use this skill to help with model selection benchmarking in LLM Engineering." diff --git a/skills/model-serving-containers/SKILL.md b/skills/model-serving-containers/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..3efdead33953158e972d7dacdbfb97b9d9318b45 --- /dev/null +++ b/skills/model-serving-containers/SKILL.md @@ -0,0 +1,29 @@ +--- +name: model-serving-containers +description: "Guidance for model serving containers in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving model serving containers, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# Model Serving Containers + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for model serving containers. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on model serving containers. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/model-serving-containers/agents/openai.yaml b/skills/model-serving-containers/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..daa4933c960cc6006098325d0e55a65029b9ef29 --- /dev/null +++ b/skills/model-serving-containers/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Model Serving Containers" +short_description: "Work on model serving containers for MLOps." +default_prompt: "Use this skill to help with model serving containers in MLOps." diff --git a/skills/mongodb-document-modeling/SKILL.md b/skills/mongodb-document-modeling/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..12b3f322616b8314b9d356eb1df63dbbe2d07964 --- /dev/null +++ b/skills/mongodb-document-modeling/SKILL.md @@ -0,0 +1,29 @@ +--- +name: mongodb-document-modeling +description: "Guidance for MongoDB document modeling in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving MongoDB document modeling, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# MongoDB Document Modeling + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for MongoDB document modeling. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on MongoDB document modeling. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/mongodb-document-modeling/agents/openai.yaml b/skills/mongodb-document-modeling/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3c77cb0497df9f8656fe63802c4fb413d4da0e76 --- /dev/null +++ b/skills/mongodb-document-modeling/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "MongoDB Document Modeling" +short_description: "Work on MongoDB document modeling for Databases And Analytics." +default_prompt: "Use this skill to help with MongoDB document modeling in Databases And Analytics." diff --git a/skills/morphological-analysis/SKILL.md b/skills/morphological-analysis/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..c600940edd64edbf9ed99bc6f31b75da02980f3a --- /dev/null +++ b/skills/morphological-analysis/SKILL.md @@ -0,0 +1,29 @@ +--- +name: morphological-analysis +description: "Guidance for morphological analysis in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving morphological analysis, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Morphological Analysis + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for morphological analysis. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on morphological analysis. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/morphological-analysis/agents/openai.yaml b/skills/morphological-analysis/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..97cd44172133956ccb1a73687677603ff5e403d9 --- /dev/null +++ b/skills/morphological-analysis/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Morphological Analysis" +short_description: "Work on morphological analysis for Natural Language Processing." +default_prompt: "Use this skill to help with morphological analysis in Natural Language Processing." diff --git a/skills/mqtt-architectures/SKILL.md b/skills/mqtt-architectures/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..8584bd91d0d9a65d1f4da956e2a1565612ce7732 --- /dev/null +++ b/skills/mqtt-architectures/SKILL.md @@ -0,0 +1,29 @@ +--- +name: mqtt-architectures +description: "Guidance for MQTT architectures in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving MQTT architectures, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# MQTT Architectures + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for MQTT architectures. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on MQTT architectures. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/mqtt-architectures/agents/openai.yaml b/skills/mqtt-architectures/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ca4f6f662a2a83d824fc413591aeeb33f0c2094d --- /dev/null +++ b/skills/mqtt-architectures/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "MQTT Architectures" +short_description: "Work on MQTT architectures for Robotics And IoT." +default_prompt: "Use this skill to help with MQTT architectures in Robotics And IoT." diff --git a/skills/multi-agent-coordination/SKILL.md b/skills/multi-agent-coordination/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..29beab0e9ced5257459b31591fa78db9b3d1b28c --- /dev/null +++ b/skills/multi-agent-coordination/SKILL.md @@ -0,0 +1,29 @@ +--- +name: multi-agent-coordination +description: "Guidance for multi agent coordination in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving multi agent coordination, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Multi Agent Coordination + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for multi agent coordination. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on multi agent coordination. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/multi-agent-coordination/agents/openai.yaml b/skills/multi-agent-coordination/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..6e94c8a43d78a2f1203831571bb4ebee6650a68c --- /dev/null +++ b/skills/multi-agent-coordination/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Multi Agent Coordination" +short_description: "Work on multi agent coordination for Agentic AI." +default_prompt: "Use this skill to help with multi agent coordination in Agentic AI." diff --git a/skills/multi-environment-config/SKILL.md b/skills/multi-environment-config/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..756f339dcac662a62df69b775fd1ab4f39965c52 --- /dev/null +++ b/skills/multi-environment-config/SKILL.md @@ -0,0 +1,29 @@ +--- +name: multi-environment-config +description: "Guidance for multi environment config in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving multi environment config, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# Multi Environment Config + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for multi environment config. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on multi environment config. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/multi-environment-config/agents/openai.yaml b/skills/multi-environment-config/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..86f71e4eb9121c9fa2ab9f39729b22816e3f23f0 --- /dev/null +++ b/skills/multi-environment-config/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Multi Environment Config" +short_description: "Work on multi environment config for Cloud And DevOps." +default_prompt: "Use this skill to help with multi environment config in Cloud And DevOps." diff --git a/skills/multi-tenant-data-models/SKILL.md b/skills/multi-tenant-data-models/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..039805df43334222a8697217a015432ad5e8d3f9 --- /dev/null +++ b/skills/multi-tenant-data-models/SKILL.md @@ -0,0 +1,29 @@ +--- +name: multi-tenant-data-models +description: "Guidance for multi tenant data models in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving multi tenant data models, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# Multi Tenant Data Models + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for multi tenant data models. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on multi tenant data models. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/multi-tenant-data-models/agents/openai.yaml b/skills/multi-tenant-data-models/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b3de7ac76c4e01e3226fc642b33068224d42864f --- /dev/null +++ b/skills/multi-tenant-data-models/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Multi Tenant Data Models" +short_description: "Work on multi tenant data models for Databases And Analytics." +default_prompt: "Use this skill to help with multi tenant data models in Databases And Analytics." diff --git a/skills/multi-tenant-model-gateways/SKILL.md b/skills/multi-tenant-model-gateways/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..c43f0970fb8081e3f27adfeb0dae5354c5cf83ba --- /dev/null +++ b/skills/multi-tenant-model-gateways/SKILL.md @@ -0,0 +1,29 @@ +--- +name: multi-tenant-model-gateways +description: "Guidance for multi tenant model gateways in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving multi tenant model gateways, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Multi Tenant Model Gateways + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for multi tenant model gateways. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on multi tenant model gateways. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/multi-tenant-model-gateways/agents/openai.yaml b/skills/multi-tenant-model-gateways/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ca132984cce484e27b7fb97678a43812c27871be --- /dev/null +++ b/skills/multi-tenant-model-gateways/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Multi Tenant Model Gateways" +short_description: "Work on multi tenant model gateways for LLM Engineering." +default_prompt: "Use this skill to help with multi tenant model gateways in LLM Engineering." diff --git a/skills/multilingual-nlp/SKILL.md b/skills/multilingual-nlp/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..736594ba46d0a18df676c53fd14d2b7b3866bdbe --- /dev/null +++ b/skills/multilingual-nlp/SKILL.md @@ -0,0 +1,29 @@ +--- +name: multilingual-nlp +description: "Guidance for multilingual NLP in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving multilingual NLP, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Multilingual NLP + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for multilingual NLP. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on multilingual NLP. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/multilingual-nlp/agents/openai.yaml b/skills/multilingual-nlp/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7494666d02497ae2321a7a09b202c745d66cbfba --- /dev/null +++ b/skills/multilingual-nlp/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Multilingual NLP" +short_description: "Work on multilingual NLP for Natural Language Processing." +default_prompt: "Use this skill to help with multilingual NLP in Natural Language Processing." diff --git a/skills/multilingual-speech/SKILL.md b/skills/multilingual-speech/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..84b29789eacfe26dae6101bff399fe7687f420ab --- /dev/null +++ b/skills/multilingual-speech/SKILL.md @@ -0,0 +1,29 @@ +--- +name: multilingual-speech +description: "Guidance for multilingual speech in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving multilingual speech, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Multilingual Speech + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for multilingual speech. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on multilingual speech. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/multilingual-speech/agents/openai.yaml b/skills/multilingual-speech/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..a6c3df86218b1befa9b3642908e9a4ba89202f29 --- /dev/null +++ b/skills/multilingual-speech/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Multilingual Speech" +short_description: "Work on multilingual speech for Speech And Audio." +default_prompt: "Use this skill to help with multilingual speech in Speech And Audio." diff --git a/skills/multimodal-evaluation/SKILL.md b/skills/multimodal-evaluation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..025faaf0e3a4c0aacccc0ef862f6591de7e2de4b --- /dev/null +++ b/skills/multimodal-evaluation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: multimodal-evaluation +description: "Guidance for multimodal evaluation in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving multimodal evaluation, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Multimodal Evaluation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for multimodal evaluation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on multimodal evaluation. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/multimodal-evaluation/agents/openai.yaml b/skills/multimodal-evaluation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..098b3382b8fde6a115f0243e1a57db062c662366 --- /dev/null +++ b/skills/multimodal-evaluation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Multimodal Evaluation" +short_description: "Work on multimodal evaluation for Multimodal AI." +default_prompt: "Use this skill to help with multimodal evaluation in Multimodal AI." diff --git a/skills/multimodal-latency-optimization/SKILL.md b/skills/multimodal-latency-optimization/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..5d5548a9a6c86008d7cbc8af2b693930542f9839 --- /dev/null +++ b/skills/multimodal-latency-optimization/SKILL.md @@ -0,0 +1,29 @@ +--- +name: multimodal-latency-optimization +description: "Guidance for multimodal latency optimization in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving multimodal latency optimization, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Multimodal Latency Optimization + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for multimodal latency optimization. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on multimodal latency optimization. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/multimodal-latency-optimization/agents/openai.yaml b/skills/multimodal-latency-optimization/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..1ebc54286300ff16bb61be3b1a954963895295f0 --- /dev/null +++ b/skills/multimodal-latency-optimization/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Multimodal Latency Optimization" +short_description: "Work on multimodal latency optimization for Multimodal AI." +default_prompt: "Use this skill to help with multimodal latency optimization in Multimodal AI." diff --git a/skills/multimodal-rag/SKILL.md b/skills/multimodal-rag/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..addfdf853a9c35a4cf7509bd363c1a9fecf01c2a --- /dev/null +++ b/skills/multimodal-rag/SKILL.md @@ -0,0 +1,29 @@ +--- +name: multimodal-rag +description: "Guidance for multimodal RAG in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving multimodal RAG, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Multimodal RAG + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for multimodal RAG. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on multimodal RAG. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/multimodal-rag/agents/openai.yaml b/skills/multimodal-rag/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..996d8a7f2b753ef1992c413054b9ce83a0ea1935 --- /dev/null +++ b/skills/multimodal-rag/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Multimodal RAG" +short_description: "Work on multimodal RAG for Multimodal AI." +default_prompt: "Use this skill to help with multimodal RAG in Multimodal AI." diff --git a/skills/multimodal-safety/SKILL.md b/skills/multimodal-safety/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..b3f12103ef1cc617394480cbac62b54198c44af1 --- /dev/null +++ b/skills/multimodal-safety/SKILL.md @@ -0,0 +1,29 @@ +--- +name: multimodal-safety +description: "Guidance for multimodal safety in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving multimodal safety, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Multimodal Safety + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for multimodal safety. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on multimodal safety. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/multimodal-safety/agents/openai.yaml b/skills/multimodal-safety/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..2dc998060e64ef1a12b403e5f8680b63f8b62102 --- /dev/null +++ b/skills/multimodal-safety/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Multimodal Safety" +short_description: "Work on multimodal safety for Multimodal AI." +default_prompt: "Use this skill to help with multimodal safety in Multimodal AI." diff --git a/skills/music-information-retrieval/SKILL.md b/skills/music-information-retrieval/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..4443cf095802d5309313a6574cf3f01e9378434a --- /dev/null +++ b/skills/music-information-retrieval/SKILL.md @@ -0,0 +1,29 @@ +--- +name: music-information-retrieval +description: "Guidance for music information retrieval in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving music information retrieval, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Music Information Retrieval + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for music information retrieval. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on music information retrieval. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/music-information-retrieval/agents/openai.yaml b/skills/music-information-retrieval/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..21ba6a2110347a5b251e71c1056436866e984912 --- /dev/null +++ b/skills/music-information-retrieval/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Music Information Retrieval" +short_description: "Work on music information retrieval for Speech And Audio." +default_prompt: "Use this skill to help with music information retrieval in Speech And Audio." diff --git a/skills/mysql-query-optimization/SKILL.md b/skills/mysql-query-optimization/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..5be9da030a63451078b86b10c14d8374ba33fb66 --- /dev/null +++ b/skills/mysql-query-optimization/SKILL.md @@ -0,0 +1,29 @@ +--- +name: mysql-query-optimization +description: "Guidance for MySQL query optimization in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving MySQL query optimization, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# MySQL Query Optimization + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for MySQL query optimization. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on MySQL query optimization. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/mysql-query-optimization/agents/openai.yaml b/skills/mysql-query-optimization/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..653265e98b7daa2180bfc49a888b43addaedb4d9 --- /dev/null +++ b/skills/mysql-query-optimization/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "MySQL Query Optimization" +short_description: "Work on MySQL query optimization for Databases And Analytics." +default_prompt: "Use this skill to help with MySQL query optimization in Databases And Analytics." diff --git a/skills/named-entity-recognition/SKILL.md b/skills/named-entity-recognition/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..f7ff3e5b1ad22d5ff0f304a3af657a6cc76c39f0 --- /dev/null +++ b/skills/named-entity-recognition/SKILL.md @@ -0,0 +1,29 @@ +--- +name: named-entity-recognition +description: "Guidance for named entity recognition in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving named entity recognition, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Named Entity Recognition + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for named entity recognition. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on named entity recognition. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/named-entity-recognition/agents/openai.yaml b/skills/named-entity-recognition/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d4471f031ddd636ed18dd96424c9aa42b3fb87b8 --- /dev/null +++ b/skills/named-entity-recognition/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Named Entity Recognition" +short_description: "Work on named entity recognition for Natural Language Processing." +default_prompt: "Use this skill to help with named entity recognition in Natural Language Processing." diff --git a/skills/networking-design/SKILL.md b/skills/networking-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..eaacc6130f23d6c285f0c105fc763564b904830c --- /dev/null +++ b/skills/networking-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: networking-design +description: "Guidance for networking design in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving networking design, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# Networking Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for networking design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on networking design. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/networking-design/agents/openai.yaml b/skills/networking-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..461a5ce832e63cb8bb5d4f5de85535e5b08f9e60 --- /dev/null +++ b/skills/networking-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Networking Design" +short_description: "Work on networking design for Cloud And DevOps." +default_prompt: "Use this skill to help with networking design in Cloud And DevOps." diff --git a/skills/neural-architecture-search/SKILL.md b/skills/neural-architecture-search/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..4bc8f2da033e0b0a04df562f5c2ee50efed934ff --- /dev/null +++ b/skills/neural-architecture-search/SKILL.md @@ -0,0 +1,29 @@ +--- +name: neural-architecture-search +description: "Guidance for neural architecture search in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving neural architecture search, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Neural Architecture Search + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for neural architecture search. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on neural architecture search. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/neural-architecture-search/agents/openai.yaml b/skills/neural-architecture-search/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d2bdc89db9a7840c1b370f085dcd7dde8269f64e --- /dev/null +++ b/skills/neural-architecture-search/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Neural Architecture Search" +short_description: "Work on neural architecture search for Deep Learning." +default_prompt: "Use this skill to help with neural architecture search in Deep Learning." diff --git a/skills/next-js-application-architecture/SKILL.md b/skills/next-js-application-architecture/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..69f535c0ddbaa9212e5edda006c699782f850bd5 --- /dev/null +++ b/skills/next-js-application-architecture/SKILL.md @@ -0,0 +1,29 @@ +--- +name: next-js-application-architecture +description: "Guidance for Next.js application architecture in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving Next.js application architecture, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Next.js Application Architecture + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for Next.js application architecture. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on Next.js application architecture. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/next-js-application-architecture/agents/openai.yaml b/skills/next-js-application-architecture/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3b4a02617d7a7704b20c7ca027e37481def94868 --- /dev/null +++ b/skills/next-js-application-architecture/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Next.js Application Architecture" +short_description: "Work on Next.js application architecture for Web Engineering." +default_prompt: "Use this skill to help with Next.js application architecture in Web Engineering." diff --git a/skills/notebook-to-pipeline-conversion/SKILL.md b/skills/notebook-to-pipeline-conversion/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..c4096fabb6985c9f306978752a50f316f07bc677 --- /dev/null +++ b/skills/notebook-to-pipeline-conversion/SKILL.md @@ -0,0 +1,29 @@ +--- +name: notebook-to-pipeline-conversion +description: "Guidance for notebook to pipeline conversion in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving notebook to pipeline conversion, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Notebook To Pipeline Conversion + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for notebook to pipeline conversion. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on notebook to pipeline conversion. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/notebook-to-pipeline-conversion/agents/openai.yaml b/skills/notebook-to-pipeline-conversion/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ec4b9bc2ca5b6648afb1736fe43ceb62a863b8f5 --- /dev/null +++ b/skills/notebook-to-pipeline-conversion/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Notebook To Pipeline Conversion" +short_description: "Work on notebook to pipeline conversion for Research And Scientific AI." +default_prompt: "Use this skill to help with notebook to pipeline conversion in Research And Scientific AI." diff --git a/skills/oauth-integration/SKILL.md b/skills/oauth-integration/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..5f4e51133aa198360c0cea7c409ff0879986a4f0 --- /dev/null +++ b/skills/oauth-integration/SKILL.md @@ -0,0 +1,29 @@ +--- +name: oauth-integration +description: "Guidance for OAuth integration in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving OAuth integration, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# OAuth Integration + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for OAuth integration. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on OAuth integration. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/oauth-integration/agents/openai.yaml b/skills/oauth-integration/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..4754f402dbc0bf0ae8d4343976c78337b784ece6 --- /dev/null +++ b/skills/oauth-integration/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "OAuth Integration" +short_description: "Work on OAuth integration for Security And Privacy." +default_prompt: "Use this skill to help with OAuth integration in Security And Privacy." diff --git a/skills/object-detection/SKILL.md b/skills/object-detection/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..738ce72bdb12911108793826909188e639bc0103 --- /dev/null +++ b/skills/object-detection/SKILL.md @@ -0,0 +1,29 @@ +--- +name: object-detection +description: "Guidance for object detection in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving object detection, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Object Detection + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for object detection. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on object detection. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/object-detection/agents/openai.yaml b/skills/object-detection/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ba9c05949e986255c26fd1b9daf0ac0bc96a87e6 --- /dev/null +++ b/skills/object-detection/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Object Detection" +short_description: "Work on object detection for Computer Vision." +default_prompt: "Use this skill to help with object detection in Computer Vision." diff --git a/skills/observability-stacks/SKILL.md b/skills/observability-stacks/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..62b8819073403445c6018da226f9d22a1ea62250 --- /dev/null +++ b/skills/observability-stacks/SKILL.md @@ -0,0 +1,29 @@ +--- +name: observability-stacks +description: "Guidance for observability stacks in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving observability stacks, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# Observability Stacks + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for observability stacks. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on observability stacks. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/observability-stacks/agents/openai.yaml b/skills/observability-stacks/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b05a1e41c7924906e45e44b1804e325bda499b6c --- /dev/null +++ b/skills/observability-stacks/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Observability Stacks" +short_description: "Work on observability stacks for Cloud And DevOps." +default_prompt: "Use this skill to help with observability stacks in Cloud And DevOps." diff --git a/skills/ocr-pipelines/SKILL.md b/skills/ocr-pipelines/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..510bb69053ea76ce5243eee013232914b3ff20c1 --- /dev/null +++ b/skills/ocr-pipelines/SKILL.md @@ -0,0 +1,29 @@ +--- +name: ocr-pipelines +description: "Guidance for OCR pipelines in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving OCR pipelines, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# OCR Pipelines + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for OCR pipelines. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on OCR pipelines. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/ocr-pipelines/agents/openai.yaml b/skills/ocr-pipelines/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..6aaaf3311ac54a473cd8739331d90340767fe062 --- /dev/null +++ b/skills/ocr-pipelines/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "OCR Pipelines" +short_description: "Work on OCR pipelines for Computer Vision." +default_prompt: "Use this skill to help with OCR pipelines in Computer Vision." diff --git a/skills/ocr-text-cleanup/SKILL.md b/skills/ocr-text-cleanup/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..d295366fc82a515ea0ba68e1912c062b88487189 --- /dev/null +++ b/skills/ocr-text-cleanup/SKILL.md @@ -0,0 +1,29 @@ +--- +name: ocr-text-cleanup +description: "Guidance for OCR text cleanup in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving OCR text cleanup, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# OCR Text Cleanup + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for OCR text cleanup. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on OCR text cleanup. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/ocr-text-cleanup/agents/openai.yaml b/skills/ocr-text-cleanup/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3cbf3e7fcc26813136aeb2db17aef4eff97aae75 --- /dev/null +++ b/skills/ocr-text-cleanup/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "OCR Text Cleanup" +short_description: "Work on OCR text cleanup for Natural Language Processing." +default_prompt: "Use this skill to help with OCR text cleanup in Natural Language Processing." diff --git a/skills/offline-eval-reporting/SKILL.md b/skills/offline-eval-reporting/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a62a62faa41020e4a6e6ea678342fcffe5a6ca33 --- /dev/null +++ b/skills/offline-eval-reporting/SKILL.md @@ -0,0 +1,29 @@ +--- +name: offline-eval-reporting +description: "Guidance for offline eval reporting in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving offline eval reporting, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# Offline Eval Reporting + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for offline eval reporting. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on offline eval reporting. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/offline-eval-reporting/agents/openai.yaml b/skills/offline-eval-reporting/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3c5b91e60ec3599969858e42c62dae653dd69182 --- /dev/null +++ b/skills/offline-eval-reporting/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Offline Eval Reporting" +short_description: "Work on offline eval reporting for Prompting And Evaluation." +default_prompt: "Use this skill to help with offline eval reporting in Prompting And Evaluation." diff --git a/skills/offline-first-mobile/SKILL.md b/skills/offline-first-mobile/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..795689fd070ded0b4210a112f334413807ebd70d --- /dev/null +++ b/skills/offline-first-mobile/SKILL.md @@ -0,0 +1,29 @@ +--- +name: offline-first-mobile +description: "Guidance for offline first mobile in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving offline first mobile, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Offline First Mobile + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for offline first mobile. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on offline first mobile. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/offline-first-mobile/agents/openai.yaml b/skills/offline-first-mobile/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..dc78a32640b021337e76a6c964645c16130245e3 --- /dev/null +++ b/skills/offline-first-mobile/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Offline First Mobile" +short_description: "Work on offline first mobile for Mobile App Engineering." +default_prompt: "Use this skill to help with offline first mobile in Mobile App Engineering." diff --git a/skills/olap-cube-modeling/SKILL.md b/skills/olap-cube-modeling/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a00200019be5ad2993c2de6d69087ff92fd26a24 --- /dev/null +++ b/skills/olap-cube-modeling/SKILL.md @@ -0,0 +1,29 @@ +--- +name: olap-cube-modeling +description: "Guidance for OLAP cube modeling in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving OLAP cube modeling, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# OLAP Cube Modeling + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for OLAP cube modeling. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on OLAP cube modeling. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/olap-cube-modeling/agents/openai.yaml b/skills/olap-cube-modeling/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..665ad9bafcf0b86d3f81bef0707f2ff777f7ed3b --- /dev/null +++ b/skills/olap-cube-modeling/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "OLAP Cube Modeling" +short_description: "Work on OLAP cube modeling for Databases And Analytics." +default_prompt: "Use this skill to help with OLAP cube modeling in Databases And Analytics." diff --git a/skills/online-eval-monitoring/SKILL.md b/skills/online-eval-monitoring/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..57ce29fd5b9d20af6e6bd66eba90b13b77e3ecdb --- /dev/null +++ b/skills/online-eval-monitoring/SKILL.md @@ -0,0 +1,29 @@ +--- +name: online-eval-monitoring +description: "Guidance for online eval monitoring in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving online eval monitoring, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# Online Eval Monitoring + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for online eval monitoring. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on online eval monitoring. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/online-eval-monitoring/agents/openai.yaml b/skills/online-eval-monitoring/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..07bb56da41cabe5ef641ee9a49eea049cd244dc7 --- /dev/null +++ b/skills/online-eval-monitoring/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Online Eval Monitoring" +short_description: "Work on online eval monitoring for Prompting And Evaluation." +default_prompt: "Use this skill to help with online eval monitoring in Prompting And Evaluation." diff --git a/skills/online-inference-services/SKILL.md b/skills/online-inference-services/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..eab5569367e64ec7eeda9139def2409f72ba352f --- /dev/null +++ b/skills/online-inference-services/SKILL.md @@ -0,0 +1,29 @@ +--- +name: online-inference-services +description: "Guidance for online inference services in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving online inference services, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# Online Inference Services + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for online inference services. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on online inference services. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/online-inference-services/agents/openai.yaml b/skills/online-inference-services/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ab1906928fc73be6c2857fb42faefbf7b8b91874 --- /dev/null +++ b/skills/online-inference-services/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Online Inference Services" +short_description: "Work on online inference services for MLOps." +default_prompt: "Use this skill to help with online inference services in MLOps." diff --git a/skills/open-source-model-release/SKILL.md b/skills/open-source-model-release/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..5e3ef4f06e3218ca0a8b136adc04aaf804030ae2 --- /dev/null +++ b/skills/open-source-model-release/SKILL.md @@ -0,0 +1,29 @@ +--- +name: open-source-model-release +description: "Guidance for open source model release in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving open source model release, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Open Source Model Release + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for open source model release. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on open source model release. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/open-source-model-release/agents/openai.yaml b/skills/open-source-model-release/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..c8f2aa5c44c83b4aefb5e75a41244980f7810562 --- /dev/null +++ b/skills/open-source-model-release/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Open Source Model Release" +short_description: "Work on open source model release for Research And Scientific AI." +default_prompt: "Use this skill to help with open source model release in Research And Scientific AI." diff --git a/skills/optimizer-selection/SKILL.md b/skills/optimizer-selection/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..256cabb70fc3fd1d5baa448f46d10b0c2cf89de1 --- /dev/null +++ b/skills/optimizer-selection/SKILL.md @@ -0,0 +1,29 @@ +--- +name: optimizer-selection +description: "Guidance for optimizer selection in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving optimizer selection, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Optimizer Selection + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for optimizer selection. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on optimizer selection. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/optimizer-selection/agents/openai.yaml b/skills/optimizer-selection/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..c6a4595cc65a94174b65102c4030d59b3c0a7ef2 --- /dev/null +++ b/skills/optimizer-selection/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Optimizer Selection" +short_description: "Work on optimizer selection for Deep Learning." +default_prompt: "Use this skill to help with optimizer selection in Deep Learning." diff --git a/skills/orchestration-with-dags/SKILL.md b/skills/orchestration-with-dags/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..b8c7cbe8dc4855c78db03a4652f51ba5144160c4 --- /dev/null +++ b/skills/orchestration-with-dags/SKILL.md @@ -0,0 +1,29 @@ +--- +name: orchestration-with-dags +description: "Guidance for orchestration with DAGs in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving orchestration with DAGs, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Orchestration With DAGs + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for orchestration with DAGs. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on orchestration with DAGs. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/orchestration-with-dags/agents/openai.yaml b/skills/orchestration-with-dags/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e72d93f8e2fb7510a9f513674554c3999bdf00d7 --- /dev/null +++ b/skills/orchestration-with-dags/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Orchestration With DAGs" +short_description: "Work on orchestration with DAGs for Data Engineering." +default_prompt: "Use this skill to help with orchestration with DAGs in Data Engineering." diff --git a/skills/pairwise-model-comparison/SKILL.md b/skills/pairwise-model-comparison/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..0bb80212d60bc5a4ec3b132af6ddf57095c8d575 --- /dev/null +++ b/skills/pairwise-model-comparison/SKILL.md @@ -0,0 +1,29 @@ +--- +name: pairwise-model-comparison +description: "Guidance for pairwise model comparison in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving pairwise model comparison, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# Pairwise Model Comparison + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for pairwise model comparison. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on pairwise model comparison. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/pairwise-model-comparison/agents/openai.yaml b/skills/pairwise-model-comparison/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..35594976e940544365d3e5b7956bf5d10f8cb5f7 --- /dev/null +++ b/skills/pairwise-model-comparison/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Pairwise Model Comparison" +short_description: "Work on pairwise model comparison for Prompting And Evaluation." +default_prompt: "Use this skill to help with pairwise model comparison in Prompting And Evaluation." diff --git a/skills/paper-reproduction/SKILL.md b/skills/paper-reproduction/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a66c999295ce7eb422d377058c377b45424586cb --- /dev/null +++ b/skills/paper-reproduction/SKILL.md @@ -0,0 +1,29 @@ +--- +name: paper-reproduction +description: "Guidance for paper reproduction in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving paper reproduction, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Paper Reproduction + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for paper reproduction. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on paper reproduction. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/paper-reproduction/agents/openai.yaml b/skills/paper-reproduction/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..aea6ab08396715356f8049425c975649dd6c4a6b --- /dev/null +++ b/skills/paper-reproduction/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Paper Reproduction" +short_description: "Work on paper reproduction for Research And Scientific AI." +default_prompt: "Use this skill to help with paper reproduction in Research And Scientific AI." diff --git a/skills/partitioning-strategy/SKILL.md b/skills/partitioning-strategy/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..6d91c962cd2065dffeb99f87d9c0a85c9ead7d17 --- /dev/null +++ b/skills/partitioning-strategy/SKILL.md @@ -0,0 +1,29 @@ +--- +name: partitioning-strategy +description: "Guidance for partitioning strategy in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving partitioning strategy, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Partitioning Strategy + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for partitioning strategy. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on partitioning strategy. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/partitioning-strategy/agents/openai.yaml b/skills/partitioning-strategy/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..6ba97b7c2db00577f7a269db6ea597a0223cd2c7 --- /dev/null +++ b/skills/partitioning-strategy/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Partitioning Strategy" +short_description: "Work on partitioning strategy for Data Engineering." +default_prompt: "Use this skill to help with partitioning strategy in Data Engineering." diff --git a/skills/path-planning/SKILL.md b/skills/path-planning/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..d493d1b6696600e49154b69300a700f32b4ac66f --- /dev/null +++ b/skills/path-planning/SKILL.md @@ -0,0 +1,29 @@ +--- +name: path-planning +description: "Guidance for path planning in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving path planning, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# Path Planning + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for path planning. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on path planning. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/path-planning/agents/openai.yaml b/skills/path-planning/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..673141c635bbc77b269d395594d67caff69a1577 --- /dev/null +++ b/skills/path-planning/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Path Planning" +short_description: "Work on path planning for Robotics And IoT." +default_prompt: "Use this skill to help with path planning in Robotics And IoT." diff --git a/skills/penetration-test-triage/SKILL.md b/skills/penetration-test-triage/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..0a4d41721e683e65dcb8667fb05422ec6a7541d9 --- /dev/null +++ b/skills/penetration-test-triage/SKILL.md @@ -0,0 +1,29 @@ +--- +name: penetration-test-triage +description: "Guidance for penetration test triage in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving penetration test triage, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# Penetration Test Triage + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for penetration test triage. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on penetration test triage. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/penetration-test-triage/agents/openai.yaml b/skills/penetration-test-triage/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..2048547fde8f82d69ab714d4c0484ed4f78f61a4 --- /dev/null +++ b/skills/penetration-test-triage/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Penetration Test Triage" +short_description: "Work on penetration test triage for Security And Privacy." +default_prompt: "Use this skill to help with penetration test triage in Security And Privacy." diff --git a/skills/personal-assistant-agents/SKILL.md b/skills/personal-assistant-agents/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..7ac4c72871aa73e9f9fdabb7791f79e412b6819a --- /dev/null +++ b/skills/personal-assistant-agents/SKILL.md @@ -0,0 +1,29 @@ +--- +name: personal-assistant-agents +description: "Guidance for personal assistant agents in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving personal assistant agents, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Personal Assistant Agents + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for personal assistant agents. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on personal assistant agents. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/personal-assistant-agents/agents/openai.yaml b/skills/personal-assistant-agents/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b7473639b40eb4fe2a354f2870526ad1c14ad622 --- /dev/null +++ b/skills/personal-assistant-agents/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Personal Assistant Agents" +short_description: "Work on personal assistant agents for Agentic AI." +default_prompt: "Use this skill to help with personal assistant agents in Agentic AI." diff --git a/skills/personal-productivity-ai/SKILL.md b/skills/personal-productivity-ai/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..be8dba432f693e84f3a1a42a4faeeaf9c02b8825 --- /dev/null +++ b/skills/personal-productivity-ai/SKILL.md @@ -0,0 +1,29 @@ +--- +name: personal-productivity-ai +description: "Guidance for personal productivity AI in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving personal productivity AI, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Personal Productivity AI + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for personal productivity AI. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on personal productivity AI. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/personal-productivity-ai/agents/openai.yaml b/skills/personal-productivity-ai/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..1da7e1978c06fe60635398900066d0cbcb3e8baa --- /dev/null +++ b/skills/personal-productivity-ai/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Personal Productivity AI" +short_description: "Work on personal productivity AI for Domain AI." +default_prompt: "Use this skill to help with personal productivity AI in Domain AI." diff --git a/skills/phoneme-alignment/SKILL.md b/skills/phoneme-alignment/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..9903467694eee96a10d659a5453996ca89497a75 --- /dev/null +++ b/skills/phoneme-alignment/SKILL.md @@ -0,0 +1,29 @@ +--- +name: phoneme-alignment +description: "Guidance for phoneme alignment in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving phoneme alignment, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Phoneme Alignment + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for phoneme alignment. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on phoneme alignment. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/phoneme-alignment/agents/openai.yaml b/skills/phoneme-alignment/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..180e580cbf19a7da0c2bdb3da8ec2df84e18cf2a --- /dev/null +++ b/skills/phoneme-alignment/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Phoneme Alignment" +short_description: "Work on phoneme alignment for Speech And Audio." +default_prompt: "Use this skill to help with phoneme alignment in Speech And Audio." diff --git a/skills/physics-informed-neural-networks/SKILL.md b/skills/physics-informed-neural-networks/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..40c0ee9687b5e59b625932359617d62fa9e36431 --- /dev/null +++ b/skills/physics-informed-neural-networks/SKILL.md @@ -0,0 +1,29 @@ +--- +name: physics-informed-neural-networks +description: "Guidance for physics informed neural networks in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving physics informed neural networks, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Physics Informed Neural Networks + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for physics informed neural networks. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on physics informed neural networks. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/physics-informed-neural-networks/agents/openai.yaml b/skills/physics-informed-neural-networks/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..77f8c5b7da8bc9072738b3840743e09bb8f0d62b --- /dev/null +++ b/skills/physics-informed-neural-networks/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Physics Informed Neural Networks" +short_description: "Work on physics informed neural networks for Research And Scientific AI." +default_prompt: "Use this skill to help with physics informed neural networks in Research And Scientific AI." diff --git a/skills/pii-minimization/SKILL.md b/skills/pii-minimization/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..40778f000564813151c384f3293caf4c929d7455 --- /dev/null +++ b/skills/pii-minimization/SKILL.md @@ -0,0 +1,29 @@ +--- +name: pii-minimization +description: "Guidance for PII minimization in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving PII minimization, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# PII Minimization + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for PII minimization. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on PII minimization. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/pii-minimization/agents/openai.yaml b/skills/pii-minimization/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..2f93df36608b1d557b5a94002dc9d55e1145773e --- /dev/null +++ b/skills/pii-minimization/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "PII Minimization" +short_description: "Work on PII minimization for Security And Privacy." +default_prompt: "Use this skill to help with PII minimization in Security And Privacy." diff --git a/skills/planner-executor-agents/SKILL.md b/skills/planner-executor-agents/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..70cbcb83f95d947022886eb52b052ce2277897b9 --- /dev/null +++ b/skills/planner-executor-agents/SKILL.md @@ -0,0 +1,29 @@ +--- +name: planner-executor-agents +description: "Guidance for planner executor agents in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving planner executor agents, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Planner Executor Agents + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for planner executor agents. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on planner executor agents. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/planner-executor-agents/agents/openai.yaml b/skills/planner-executor-agents/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..a5e9e3360215ddf2e5c37dc76c8d339464bcb9cb --- /dev/null +++ b/skills/planner-executor-agents/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Planner Executor Agents" +short_description: "Work on planner executor agents for Agentic AI." +default_prompt: "Use this skill to help with planner executor agents in Agentic AI." diff --git a/skills/podcast-processing/SKILL.md b/skills/podcast-processing/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..f9c02d4ef8415b3c5d1582154ef486758034b9d3 --- /dev/null +++ b/skills/podcast-processing/SKILL.md @@ -0,0 +1,29 @@ +--- +name: podcast-processing +description: "Guidance for podcast processing in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving podcast processing, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Podcast Processing + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for podcast processing. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on podcast processing. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/podcast-processing/agents/openai.yaml b/skills/podcast-processing/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d0f43ba90790b1952ed3de2a4be0c0f598ee7588 --- /dev/null +++ b/skills/podcast-processing/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Podcast Processing" +short_description: "Work on podcast processing for Speech And Audio." +default_prompt: "Use this skill to help with podcast processing in Speech And Audio." diff --git a/skills/pose-estimation/SKILL.md b/skills/pose-estimation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..218f92a56b23fcadfcdc10aa8cfb7a55b8e845ec --- /dev/null +++ b/skills/pose-estimation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: pose-estimation +description: "Guidance for pose estimation in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving pose estimation, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Pose Estimation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for pose estimation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on pose estimation. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/pose-estimation/agents/openai.yaml b/skills/pose-estimation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..5f78739046c612db06bdf8d3090da783f263d68f --- /dev/null +++ b/skills/pose-estimation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Pose Estimation" +short_description: "Work on pose estimation for Computer Vision." +default_prompt: "Use this skill to help with pose estimation in Computer Vision." diff --git a/skills/postgresql-schema-design/SKILL.md b/skills/postgresql-schema-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..751ea49002b8a81bf4df135dd68ebf3e71422eb1 --- /dev/null +++ b/skills/postgresql-schema-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: postgresql-schema-design +description: "Guidance for PostgreSQL schema design in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving PostgreSQL schema design, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# PostgreSQL Schema Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for PostgreSQL schema design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on PostgreSQL schema design. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/postgresql-schema-design/agents/openai.yaml b/skills/postgresql-schema-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..1fdcf1b6f026773c597baa706e0a80f5ebfb7ccc --- /dev/null +++ b/skills/postgresql-schema-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "PostgreSQL Schema Design" +short_description: "Work on PostgreSQL schema design for Databases And Analytics." +default_prompt: "Use this skill to help with PostgreSQL schema design in Databases And Analytics." diff --git a/skills/predictive-maintenance/SKILL.md b/skills/predictive-maintenance/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..be2a6442598daa0efdd74232ac6bba099a37f511 --- /dev/null +++ b/skills/predictive-maintenance/SKILL.md @@ -0,0 +1,29 @@ +--- +name: predictive-maintenance +description: "Guidance for predictive maintenance in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving predictive maintenance, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# Predictive Maintenance + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for predictive maintenance. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on predictive maintenance. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/predictive-maintenance/agents/openai.yaml b/skills/predictive-maintenance/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..fe1d36dcf7f4af72c9234193c98c6d48360ab0e2 --- /dev/null +++ b/skills/predictive-maintenance/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Predictive Maintenance" +short_description: "Work on predictive maintenance for Robotics And IoT." +default_prompt: "Use this skill to help with predictive maintenance in Robotics And IoT." diff --git a/skills/privacy-aware-datasets/SKILL.md b/skills/privacy-aware-datasets/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..f9326cbed560c2dbfe8911d752965541274f81a7 --- /dev/null +++ b/skills/privacy-aware-datasets/SKILL.md @@ -0,0 +1,29 @@ +--- +name: privacy-aware-datasets +description: "Guidance for privacy aware datasets in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving privacy aware datasets, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Privacy Aware Datasets + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for privacy aware datasets. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on privacy aware datasets. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/privacy-aware-datasets/agents/openai.yaml b/skills/privacy-aware-datasets/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..4bf77c6cc1d1dfed3f9649339e78ccea65439432 --- /dev/null +++ b/skills/privacy-aware-datasets/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Privacy Aware Datasets" +short_description: "Work on privacy aware datasets for Data Engineering." +default_prompt: "Use this skill to help with privacy aware datasets in Data Engineering." diff --git a/skills/privacy-impact-review/SKILL.md b/skills/privacy-impact-review/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..0b0fc82623a121cf471b89c64d535d3e5f726afa --- /dev/null +++ b/skills/privacy-impact-review/SKILL.md @@ -0,0 +1,29 @@ +--- +name: privacy-impact-review +description: "Guidance for privacy impact review in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving privacy impact review, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# Privacy Impact Review + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for privacy impact review. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on privacy impact review. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/privacy-impact-review/agents/openai.yaml b/skills/privacy-impact-review/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..bef21370cadbd5d0f9268f38830a4c85fd7f157b --- /dev/null +++ b/skills/privacy-impact-review/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Privacy Impact Review" +short_description: "Work on privacy impact review for Security And Privacy." +default_prompt: "Use this skill to help with privacy impact review in Security And Privacy." diff --git a/skills/privacy-preserving-ml/SKILL.md b/skills/privacy-preserving-ml/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..511807b1ffa834e1f0f9d67fdd25551e92cdb8ef --- /dev/null +++ b/skills/privacy-preserving-ml/SKILL.md @@ -0,0 +1,29 @@ +--- +name: privacy-preserving-ml +description: "Guidance for privacy preserving ML in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving privacy preserving ML, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# Privacy Preserving ML + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for privacy preserving ML. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on privacy preserving ML. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/privacy-preserving-ml/agents/openai.yaml b/skills/privacy-preserving-ml/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..69ebd88fcedf46da2a709030150f54fe7b1f1bf3 --- /dev/null +++ b/skills/privacy-preserving-ml/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Privacy Preserving ML" +short_description: "Work on privacy preserving ML for MLOps." +default_prompt: "Use this skill to help with privacy preserving ML in MLOps." diff --git a/skills/procurement-ai/SKILL.md b/skills/procurement-ai/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..4bfac0b86f60f9cc1e6a6748735c44bd6fe75bba --- /dev/null +++ b/skills/procurement-ai/SKILL.md @@ -0,0 +1,29 @@ +--- +name: procurement-ai +description: "Guidance for procurement AI in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving procurement AI, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Procurement AI + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for procurement AI. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on procurement AI. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/procurement-ai/agents/openai.yaml b/skills/procurement-ai/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ce65532e49dcb776e1865cb702c83f24b8ad23ae --- /dev/null +++ b/skills/procurement-ai/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Procurement AI" +short_description: "Work on procurement AI for Domain AI." +default_prompt: "Use this skill to help with procurement AI in Domain AI." diff --git a/skills/product-image-search/SKILL.md b/skills/product-image-search/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..7b1fdc3f29ce34acc2440424b72263b1dfc1177b --- /dev/null +++ b/skills/product-image-search/SKILL.md @@ -0,0 +1,29 @@ +--- +name: product-image-search +description: "Guidance for product image search in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving product image search, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Product Image Search + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for product image search. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on product image search. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/product-image-search/agents/openai.yaml b/skills/product-image-search/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..872b54248f631a253c39a443e74e00d6d89458ff --- /dev/null +++ b/skills/product-image-search/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Product Image Search" +short_description: "Work on product image search for Multimodal AI." +default_prompt: "Use this skill to help with product image search in Multimodal AI." diff --git a/skills/production-scoring/SKILL.md b/skills/production-scoring/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..ca7172f78587835cb8ab7e0a79ad4bf05577fdbd --- /dev/null +++ b/skills/production-scoring/SKILL.md @@ -0,0 +1,29 @@ +--- +name: production-scoring +description: "Guidance for production scoring in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving production scoring, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Production Scoring + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for production scoring. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on production scoring. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/production-scoring/agents/openai.yaml b/skills/production-scoring/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..5b1feee1cdad69652f4f8e7c6ddbfa5b6ca278cb --- /dev/null +++ b/skills/production-scoring/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Production Scoring" +short_description: "Work on production scoring for Machine Learning." +default_prompt: "Use this skill to help with production scoring in Machine Learning." diff --git a/skills/progressive-web-apps/SKILL.md b/skills/progressive-web-apps/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..c82330110079dee43aed67fb6927bcc3fe143f98 --- /dev/null +++ b/skills/progressive-web-apps/SKILL.md @@ -0,0 +1,29 @@ +--- +name: progressive-web-apps +description: "Guidance for progressive web apps in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving progressive web apps, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Progressive Web Apps + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for progressive web apps. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on progressive web apps. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/progressive-web-apps/agents/openai.yaml b/skills/progressive-web-apps/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b5ad85486777735a28d83d17a3d806998e15580e --- /dev/null +++ b/skills/progressive-web-apps/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Progressive Web Apps" +short_description: "Work on progressive web apps for Web Engineering." +default_prompt: "Use this skill to help with progressive web apps in Web Engineering." diff --git a/skills/prompt-cost-profiling/SKILL.md b/skills/prompt-cost-profiling/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..b906b41dab4b9525cf861a1e11d8f9b139149208 --- /dev/null +++ b/skills/prompt-cost-profiling/SKILL.md @@ -0,0 +1,29 @@ +--- +name: prompt-cost-profiling +description: "Guidance for prompt cost profiling in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving prompt cost profiling, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# Prompt Cost Profiling + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for prompt cost profiling. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on prompt cost profiling. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/prompt-cost-profiling/agents/openai.yaml b/skills/prompt-cost-profiling/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..914e227634bc17746f5ea306d57b28e94c354433 --- /dev/null +++ b/skills/prompt-cost-profiling/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Prompt Cost Profiling" +short_description: "Work on prompt cost profiling for Prompting And Evaluation." +default_prompt: "Use this skill to help with prompt cost profiling in Prompting And Evaluation." diff --git a/skills/prompt-governance/SKILL.md b/skills/prompt-governance/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..0eeda1193ef0753928f4dd266a79b6cd3c0a0df8 --- /dev/null +++ b/skills/prompt-governance/SKILL.md @@ -0,0 +1,29 @@ +--- +name: prompt-governance +description: "Guidance for prompt governance in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving prompt governance, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# Prompt Governance + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for prompt governance. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on prompt governance. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/prompt-governance/agents/openai.yaml b/skills/prompt-governance/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..1943f184b99d3aae16301b6d9e3b9541d9762f51 --- /dev/null +++ b/skills/prompt-governance/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Prompt Governance" +short_description: "Work on prompt governance for Prompting And Evaluation." +default_prompt: "Use this skill to help with prompt governance in Prompting And Evaluation." diff --git a/skills/prompt-injection-defense/SKILL.md b/skills/prompt-injection-defense/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..ff20ad00e55bad1153d6483ddf09b7583c72e9a1 --- /dev/null +++ b/skills/prompt-injection-defense/SKILL.md @@ -0,0 +1,29 @@ +--- +name: prompt-injection-defense +description: "Guidance for prompt injection defense in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving prompt injection defense, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Prompt Injection Defense + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for prompt injection defense. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on prompt injection defense. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/prompt-injection-defense/agents/openai.yaml b/skills/prompt-injection-defense/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..db1cb65a9dd9c5ee6c439bdf977c21d47855295a --- /dev/null +++ b/skills/prompt-injection-defense/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Prompt Injection Defense" +short_description: "Work on prompt injection defense for LLM Engineering." +default_prompt: "Use this skill to help with prompt injection defense in LLM Engineering." diff --git a/skills/prompt-latency-profiling/SKILL.md b/skills/prompt-latency-profiling/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..97cb5e1dc29b66823246b0193c6ab80b4c95dbe3 --- /dev/null +++ b/skills/prompt-latency-profiling/SKILL.md @@ -0,0 +1,29 @@ +--- +name: prompt-latency-profiling +description: "Guidance for prompt latency profiling in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving prompt latency profiling, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# Prompt Latency Profiling + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for prompt latency profiling. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on prompt latency profiling. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/prompt-latency-profiling/agents/openai.yaml b/skills/prompt-latency-profiling/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e5455c7c9a72a250670822a72c9c09cbb4340c51 --- /dev/null +++ b/skills/prompt-latency-profiling/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Prompt Latency Profiling" +short_description: "Work on prompt latency profiling for Prompting And Evaluation." +default_prompt: "Use this skill to help with prompt latency profiling in Prompting And Evaluation." diff --git a/skills/prompt-library-ux/SKILL.md b/skills/prompt-library-ux/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..02b89e5b80f89458bc60d844a539cf5dfc53130e --- /dev/null +++ b/skills/prompt-library-ux/SKILL.md @@ -0,0 +1,29 @@ +--- +name: prompt-library-ux +description: "Guidance for prompt library UX in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving prompt library UX, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# Prompt Library UX + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for prompt library UX. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on prompt library UX. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/prompt-library-ux/agents/openai.yaml b/skills/prompt-library-ux/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..95ddba3e81972508b601121f756fc254083c21e0 --- /dev/null +++ b/skills/prompt-library-ux/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Prompt Library UX" +short_description: "Work on prompt library UX for AI Product And UX." +default_prompt: "Use this skill to help with prompt library UX in AI Product And UX." diff --git a/skills/prompt-localization/SKILL.md b/skills/prompt-localization/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..3c2132486e05a8732bd5e971fa3dd79a2568b214 --- /dev/null +++ b/skills/prompt-localization/SKILL.md @@ -0,0 +1,29 @@ +--- +name: prompt-localization +description: "Guidance for prompt localization in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving prompt localization, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# Prompt Localization + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for prompt localization. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on prompt localization. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/prompt-localization/agents/openai.yaml b/skills/prompt-localization/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..4aae8cb6d3eb8c278a673693f6018494908d9afe --- /dev/null +++ b/skills/prompt-localization/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Prompt Localization" +short_description: "Work on prompt localization for Prompting And Evaluation." +default_prompt: "Use this skill to help with prompt localization in Prompting And Evaluation." diff --git a/skills/prompt-migration/SKILL.md b/skills/prompt-migration/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..c9e600978be833094f64cfe532873a292195f6bb --- /dev/null +++ b/skills/prompt-migration/SKILL.md @@ -0,0 +1,29 @@ +--- +name: prompt-migration +description: "Guidance for prompt migration in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving prompt migration, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# Prompt Migration + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for prompt migration. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on prompt migration. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/prompt-migration/agents/openai.yaml b/skills/prompt-migration/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e1d5afcf4cb0e566f8e3f60193cc41782cfde509 --- /dev/null +++ b/skills/prompt-migration/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Prompt Migration" +short_description: "Work on prompt migration for Prompting And Evaluation." +default_prompt: "Use this skill to help with prompt migration in Prompting And Evaluation." diff --git a/skills/prompt-test-cases/SKILL.md b/skills/prompt-test-cases/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..1c06e1f8ce849c3cfc5b39930b737ce0e4adf0e0 --- /dev/null +++ b/skills/prompt-test-cases/SKILL.md @@ -0,0 +1,29 @@ +--- +name: prompt-test-cases +description: "Guidance for prompt test cases in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving prompt test cases, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# Prompt Test Cases + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for prompt test cases. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on prompt test cases. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/prompt-test-cases/agents/openai.yaml b/skills/prompt-test-cases/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..0c8d6145f56e6a4171b05b7a7423d8b772245bb6 --- /dev/null +++ b/skills/prompt-test-cases/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Prompt Test Cases" +short_description: "Work on prompt test cases for Prompting And Evaluation." +default_prompt: "Use this skill to help with prompt test cases in Prompting And Evaluation." diff --git a/skills/prompt-versioning/SKILL.md b/skills/prompt-versioning/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..b386932a5309c7c4da37a233070f20115cc7c641 --- /dev/null +++ b/skills/prompt-versioning/SKILL.md @@ -0,0 +1,29 @@ +--- +name: prompt-versioning +description: "Guidance for prompt versioning in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving prompt versioning, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# Prompt Versioning + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for prompt versioning. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on prompt versioning. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/prompt-versioning/agents/openai.yaml b/skills/prompt-versioning/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..60e1ea249ff9291c2189aefc124f78a88c46d935 --- /dev/null +++ b/skills/prompt-versioning/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Prompt Versioning" +short_description: "Work on prompt versioning for Prompting And Evaluation." +default_prompt: "Use this skill to help with prompt versioning in Prompting And Evaluation." diff --git a/skills/prosody-control/SKILL.md b/skills/prosody-control/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a80f65b21d100b45069ad6f0fe426442184c8fa3 --- /dev/null +++ b/skills/prosody-control/SKILL.md @@ -0,0 +1,29 @@ +--- +name: prosody-control +description: "Guidance for prosody control in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving prosody control, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Prosody Control + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for prosody control. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on prosody control. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/prosody-control/agents/openai.yaml b/skills/prosody-control/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d00c43bfb2a3b990e7ce21b53367c67a3fa864b3 --- /dev/null +++ b/skills/prosody-control/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Prosody Control" +short_description: "Work on prosody control for Speech And Audio." +default_prompt: "Use this skill to help with prosody control in Speech And Audio." diff --git a/skills/public-sector-ai-workflows/SKILL.md b/skills/public-sector-ai-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..87dfea788eca645f2614a31397e8600cec7ae3a5 --- /dev/null +++ b/skills/public-sector-ai-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: public-sector-ai-workflows +description: "Guidance for public sector AI workflows in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving public sector AI workflows, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Public Sector AI Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for public sector AI workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on public sector AI workflows. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/public-sector-ai-workflows/agents/openai.yaml b/skills/public-sector-ai-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3d22df792951aac2552d3d5147473c6d297966e3 --- /dev/null +++ b/skills/public-sector-ai-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Public Sector AI Workflows" +short_description: "Work on public sector AI workflows for Domain AI." +default_prompt: "Use this skill to help with public sector AI workflows in Domain AI." diff --git a/skills/push-notifications/SKILL.md b/skills/push-notifications/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..282137f8fa13ac0af8588ee170618a10598942b6 --- /dev/null +++ b/skills/push-notifications/SKILL.md @@ -0,0 +1,29 @@ +--- +name: push-notifications +description: "Guidance for push notifications in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving push notifications, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Push Notifications + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for push notifications. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on push notifications. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/push-notifications/agents/openai.yaml b/skills/push-notifications/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..31c00d3ccadf39998f411ac594d82fd9a9e37bda --- /dev/null +++ b/skills/push-notifications/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Push Notifications" +short_description: "Work on push notifications for Mobile App Engineering." +default_prompt: "Use this skill to help with push notifications in Mobile App Engineering." diff --git a/skills/query-plan-analysis/SKILL.md b/skills/query-plan-analysis/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..dc9275e39b913b702c1fdf4e6769332ca33537f5 --- /dev/null +++ b/skills/query-plan-analysis/SKILL.md @@ -0,0 +1,29 @@ +--- +name: query-plan-analysis +description: "Guidance for query plan analysis in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving query plan analysis, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# Query Plan Analysis + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for query plan analysis. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on query plan analysis. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/query-plan-analysis/agents/openai.yaml b/skills/query-plan-analysis/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..0e906b9c66f0e1bbd590bd948a35a822337a75fa --- /dev/null +++ b/skills/query-plan-analysis/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Query Plan Analysis" +short_description: "Work on query plan analysis for Databases And Analytics." +default_prompt: "Use this skill to help with query plan analysis in Databases And Analytics." diff --git a/skills/question-answering/SKILL.md b/skills/question-answering/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..22c9174e568d7b968d550a856dce68344cca438e --- /dev/null +++ b/skills/question-answering/SKILL.md @@ -0,0 +1,29 @@ +--- +name: question-answering +description: "Guidance for question answering in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving question answering, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Question Answering + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for question answering. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on question answering. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/question-answering/agents/openai.yaml b/skills/question-answering/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..2059dfbb2c8a72d9f5783a967f0b14c49d04be12 --- /dev/null +++ b/skills/question-answering/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Question Answering" +short_description: "Work on question answering for Natural Language Processing." +default_prompt: "Use this skill to help with question answering in Natural Language Processing." diff --git a/skills/ranking-models/SKILL.md b/skills/ranking-models/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..bc640cd643dde2202c9db3eceeb3fc8418988194 --- /dev/null +++ b/skills/ranking-models/SKILL.md @@ -0,0 +1,29 @@ +--- +name: ranking-models +description: "Guidance for ranking models in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving ranking models, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Ranking Models + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for ranking models. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on ranking models. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/ranking-models/agents/openai.yaml b/skills/ranking-models/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..2d9250d1b46c6b09e51ca02512220a10b7e89243 --- /dev/null +++ b/skills/ranking-models/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Ranking Models" +short_description: "Work on ranking models for Machine Learning." +default_prompt: "Use this skill to help with ranking models in Machine Learning." diff --git a/skills/rate-limit-resilience/SKILL.md b/skills/rate-limit-resilience/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..7d63e5de897ff3ad140998a4f8c7b19b0338cbb3 --- /dev/null +++ b/skills/rate-limit-resilience/SKILL.md @@ -0,0 +1,29 @@ +--- +name: rate-limit-resilience +description: "Guidance for rate limit resilience in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving rate limit resilience, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Rate Limit Resilience + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for rate limit resilience. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on rate limit resilience. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/rate-limit-resilience/agents/openai.yaml b/skills/rate-limit-resilience/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..a9e480c674223d8267d86c407315c308b912558f --- /dev/null +++ b/skills/rate-limit-resilience/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Rate Limit Resilience" +short_description: "Work on rate limit resilience for LLM Engineering." +default_prompt: "Use this skill to help with rate limit resilience in LLM Engineering." diff --git a/skills/rate-limiting/SKILL.md b/skills/rate-limiting/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..d641dcd64fe99b90aae48d2b3ad34f7b86375189 --- /dev/null +++ b/skills/rate-limiting/SKILL.md @@ -0,0 +1,29 @@ +--- +name: rate-limiting +description: "Guidance for rate limiting in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving rate limiting, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# Rate Limiting + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for rate limiting. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on rate limiting. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/rate-limiting/agents/openai.yaml b/skills/rate-limiting/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..57cab3a8f4520ea32cc743769ba276149aab565d --- /dev/null +++ b/skills/rate-limiting/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Rate Limiting" +short_description: "Work on rate limiting for Security And Privacy." +default_prompt: "Use this skill to help with rate limiting in Security And Privacy." diff --git a/skills/react-application-architecture/SKILL.md b/skills/react-application-architecture/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..6009dce4a0ca632365edebf9465fa2c61fec1400 --- /dev/null +++ b/skills/react-application-architecture/SKILL.md @@ -0,0 +1,29 @@ +--- +name: react-application-architecture +description: "Guidance for React application architecture in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving React application architecture, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# React Application Architecture + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for React application architecture. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on React application architecture. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/react-application-architecture/agents/openai.yaml b/skills/react-application-architecture/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e9d91f1f3b659b7570a485ae099ff2c6de7bf157 --- /dev/null +++ b/skills/react-application-architecture/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "React Application Architecture" +short_description: "Work on React application architecture for Web Engineering." +default_prompt: "Use this skill to help with React application architecture in Web Engineering." diff --git a/skills/react-native-apps/SKILL.md b/skills/react-native-apps/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..49dc2e28543b489f60c00fb5896c59a694108ae5 --- /dev/null +++ b/skills/react-native-apps/SKILL.md @@ -0,0 +1,29 @@ +--- +name: react-native-apps +description: "Guidance for React Native apps in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving React Native apps, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# React Native Apps + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for React Native apps. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on React Native apps. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/react-native-apps/agents/openai.yaml b/skills/react-native-apps/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ca3da0ffc54e70d6a71b16a536df46d7560eec4a --- /dev/null +++ b/skills/react-native-apps/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "React Native Apps" +short_description: "Work on React Native apps for Mobile App Engineering." +default_prompt: "Use this skill to help with React Native apps in Mobile App Engineering." diff --git a/skills/react-style-reasoning-loops/SKILL.md b/skills/react-style-reasoning-loops/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..78632b4e5d113742b0e67ed75057fd6b4c36195c --- /dev/null +++ b/skills/react-style-reasoning-loops/SKILL.md @@ -0,0 +1,29 @@ +--- +name: react-style-reasoning-loops +description: "Guidance for react style reasoning loops in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving react style reasoning loops, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# React Style Reasoning Loops + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for react style reasoning loops. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on react style reasoning loops. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/react-style-reasoning-loops/agents/openai.yaml b/skills/react-style-reasoning-loops/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..2a9e4fb0c18785b80f727a1ee59c1caa2eeb2340 --- /dev/null +++ b/skills/react-style-reasoning-loops/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "React Style Reasoning Loops" +short_description: "Work on react style reasoning loops for Agentic AI." +default_prompt: "Use this skill to help with react style reasoning loops in Agentic AI." diff --git a/skills/real-estate-ai-workflows/SKILL.md b/skills/real-estate-ai-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..ee1c861d5beafb70c9dad94bd9aa8c11396b6dbf --- /dev/null +++ b/skills/real-estate-ai-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: real-estate-ai-workflows +description: "Guidance for real estate AI workflows in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving real estate AI workflows, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Real Estate AI Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for real estate AI workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on real estate AI workflows. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/real-estate-ai-workflows/agents/openai.yaml b/skills/real-estate-ai-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..6509f5e96c2797d0f743f68fe36c2deef72ab9f0 --- /dev/null +++ b/skills/real-estate-ai-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Real Estate AI Workflows" +short_description: "Work on real estate AI workflows for Domain AI." +default_prompt: "Use this skill to help with real estate AI workflows in Domain AI." diff --git a/skills/real-time-audio-inference/SKILL.md b/skills/real-time-audio-inference/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..114b5fe4f4cd8dc0f7ceaf7e5e617a5ccbb38bd8 --- /dev/null +++ b/skills/real-time-audio-inference/SKILL.md @@ -0,0 +1,29 @@ +--- +name: real-time-audio-inference +description: "Guidance for real time audio inference in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving real time audio inference, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Real Time Audio Inference + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for real time audio inference. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on real time audio inference. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/real-time-audio-inference/agents/openai.yaml b/skills/real-time-audio-inference/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..68b085fb71ccfadeb2dc86b7acabdfb8de9bad3b --- /dev/null +++ b/skills/real-time-audio-inference/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Real Time Audio Inference" +short_description: "Work on real time audio inference for Speech And Audio." +default_prompt: "Use this skill to help with real time audio inference in Speech And Audio." diff --git a/skills/realtime-dashboards/SKILL.md b/skills/realtime-dashboards/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..7ac8d7ade37158fb32142fdf965b67a2d6827511 --- /dev/null +++ b/skills/realtime-dashboards/SKILL.md @@ -0,0 +1,29 @@ +--- +name: realtime-dashboards +description: "Guidance for realtime dashboards in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving realtime dashboards, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Realtime Dashboards + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for realtime dashboards. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on realtime dashboards. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/realtime-dashboards/agents/openai.yaml b/skills/realtime-dashboards/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..395e38a9581ec577259d0205100626aceff11e94 --- /dev/null +++ b/skills/realtime-dashboards/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Realtime Dashboards" +short_description: "Work on realtime dashboards for Data Engineering." +default_prompt: "Use this skill to help with realtime dashboards in Data Engineering." diff --git a/skills/recommendation-systems/SKILL.md b/skills/recommendation-systems/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..1abd2e9e701fa37ad8109c28687e475263295ed2 --- /dev/null +++ b/skills/recommendation-systems/SKILL.md @@ -0,0 +1,29 @@ +--- +name: recommendation-systems +description: "Guidance for recommendation systems in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving recommendation systems, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Recommendation Systems + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for recommendation systems. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on recommendation systems. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/recommendation-systems/agents/openai.yaml b/skills/recommendation-systems/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..526a8c77759639138e034156cf4397cbb084a975 --- /dev/null +++ b/skills/recommendation-systems/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Recommendation Systems" +short_description: "Work on recommendation systems for Machine Learning." +default_prompt: "Use this skill to help with recommendation systems in Machine Learning." diff --git a/skills/red-team-planning/SKILL.md b/skills/red-team-planning/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..b2be97fac76d3fcb3d0e94de107d09adcb93178a --- /dev/null +++ b/skills/red-team-planning/SKILL.md @@ -0,0 +1,29 @@ +--- +name: red-team-planning +description: "Guidance for red team planning in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving red team planning, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# Red Team Planning + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for red team planning. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on red team planning. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/red-team-planning/agents/openai.yaml b/skills/red-team-planning/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..826ae5aa3d2912241491f53e2a4d0540e0f6f433 --- /dev/null +++ b/skills/red-team-planning/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Red Team Planning" +short_description: "Work on red team planning for Security And Privacy." +default_prompt: "Use this skill to help with red team planning in Security And Privacy." diff --git a/skills/redis-caching/SKILL.md b/skills/redis-caching/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..738a4eccf5bb8a773aab752a46ff18a2ad0f087f --- /dev/null +++ b/skills/redis-caching/SKILL.md @@ -0,0 +1,29 @@ +--- +name: redis-caching +description: "Guidance for Redis caching in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving Redis caching, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# Redis Caching + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for Redis caching. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on Redis caching. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/redis-caching/agents/openai.yaml b/skills/redis-caching/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d2e7dc79def3bb3b4e17c4b27fa3a8ba133923e7 --- /dev/null +++ b/skills/redis-caching/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Redis Caching" +short_description: "Work on Redis caching for Databases And Analytics." +default_prompt: "Use this skill to help with Redis caching in Databases And Analytics." diff --git a/skills/regression-eval-suites/SKILL.md b/skills/regression-eval-suites/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..59f177550ffcdbe79daaf9302473fc532c5b546c --- /dev/null +++ b/skills/regression-eval-suites/SKILL.md @@ -0,0 +1,29 @@ +--- +name: regression-eval-suites +description: "Guidance for regression eval suites in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving regression eval suites, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# Regression Eval Suites + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for regression eval suites. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on regression eval suites. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/regression-eval-suites/agents/openai.yaml b/skills/regression-eval-suites/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..09dc7c633f3a0cd51c43392f740ab0302086b512 --- /dev/null +++ b/skills/regression-eval-suites/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Regression Eval Suites" +short_description: "Work on regression eval suites for Prompting And Evaluation." +default_prompt: "Use this skill to help with regression eval suites in Prompting And Evaluation." diff --git a/skills/regularization-strategy/SKILL.md b/skills/regularization-strategy/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..4378788fafd14f293150cc24dbb2212e19f9164a --- /dev/null +++ b/skills/regularization-strategy/SKILL.md @@ -0,0 +1,29 @@ +--- +name: regularization-strategy +description: "Guidance for regularization strategy in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving regularization strategy, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Regularization Strategy + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for regularization strategy. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on regularization strategy. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/regularization-strategy/agents/openai.yaml b/skills/regularization-strategy/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3b59c84833ef3ad723e4af31432d3099b673394c --- /dev/null +++ b/skills/regularization-strategy/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Regularization Strategy" +short_description: "Work on regularization strategy for Deep Learning." +default_prompt: "Use this skill to help with regularization strategy in Deep Learning." diff --git a/skills/relation-extraction/SKILL.md b/skills/relation-extraction/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..095dab07d2bd5a411ffd7af2f28a4f4d0dd5f86f --- /dev/null +++ b/skills/relation-extraction/SKILL.md @@ -0,0 +1,29 @@ +--- +name: relation-extraction +description: "Guidance for relation extraction in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving relation extraction, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Relation Extraction + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for relation extraction. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on relation extraction. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/relation-extraction/agents/openai.yaml b/skills/relation-extraction/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..c4d9c7389e1465e54bdc247d877046c670b5d7f8 --- /dev/null +++ b/skills/relation-extraction/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Relation Extraction" +short_description: "Work on relation extraction for Natural Language Processing." +default_prompt: "Use this skill to help with relation extraction in Natural Language Processing." diff --git a/skills/replication-strategy/SKILL.md b/skills/replication-strategy/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..f1d746167236625e63c39e6bdabe5ac61778b97b --- /dev/null +++ b/skills/replication-strategy/SKILL.md @@ -0,0 +1,29 @@ +--- +name: replication-strategy +description: "Guidance for replication strategy in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving replication strategy, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# Replication Strategy + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for replication strategy. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on replication strategy. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/replication-strategy/agents/openai.yaml b/skills/replication-strategy/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..c55659f590d03ea3d82bc563a66203a4da1fffef --- /dev/null +++ b/skills/replication-strategy/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Replication Strategy" +short_description: "Work on replication strategy for Databases And Analytics." +default_prompt: "Use this skill to help with replication strategy in Databases And Analytics." diff --git a/skills/reproducibility-audits/SKILL.md b/skills/reproducibility-audits/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..6eb5aa6870ce7835af33bc5e49585f93ec918f83 --- /dev/null +++ b/skills/reproducibility-audits/SKILL.md @@ -0,0 +1,29 @@ +--- +name: reproducibility-audits +description: "Guidance for reproducibility audits in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving reproducibility audits, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Reproducibility Audits + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for reproducibility audits. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on reproducibility audits. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/reproducibility-audits/agents/openai.yaml b/skills/reproducibility-audits/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e95ab70bfbf9e5ac51b7597db01106a0c1fd3231 --- /dev/null +++ b/skills/reproducibility-audits/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Reproducibility Audits" +short_description: "Work on reproducibility audits for Research And Scientific AI." +default_prompt: "Use this skill to help with reproducibility audits in Research And Scientific AI." diff --git a/skills/reproducible-training/SKILL.md b/skills/reproducible-training/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..1abac2e5e2c0df047d95e87cfcedf3e2e83a524b --- /dev/null +++ b/skills/reproducible-training/SKILL.md @@ -0,0 +1,29 @@ +--- +name: reproducible-training +description: "Guidance for reproducible training in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving reproducible training, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# Reproducible Training + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for reproducible training. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on reproducible training. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/reproducible-training/agents/openai.yaml b/skills/reproducible-training/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..67cb364e73105304dadd4f07fe47e1e1012cf510 --- /dev/null +++ b/skills/reproducible-training/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Reproducible Training" +short_description: "Work on reproducible training for MLOps." +default_prompt: "Use this skill to help with reproducible training in MLOps." diff --git a/skills/research-agent-workflows/SKILL.md b/skills/research-agent-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..57c27e14448d68cfcddb42e19c05cde1bf86e402 --- /dev/null +++ b/skills/research-agent-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: research-agent-workflows +description: "Guidance for research agent workflows in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving research agent workflows, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Research Agent Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for research agent workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on research agent workflows. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/research-agent-workflows/agents/openai.yaml b/skills/research-agent-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..480740d71e8f11eae3a26470bea3da65614363c0 --- /dev/null +++ b/skills/research-agent-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Research Agent Workflows" +short_description: "Work on research agent workflows for Agentic AI." +default_prompt: "Use this skill to help with research agent workflows in Agentic AI." diff --git a/skills/research-artifact-review/SKILL.md b/skills/research-artifact-review/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..68cdb590c4aa6c0a5300a86235f8bdcb2341a0d7 --- /dev/null +++ b/skills/research-artifact-review/SKILL.md @@ -0,0 +1,29 @@ +--- +name: research-artifact-review +description: "Guidance for research artifact review in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving research artifact review, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Research Artifact Review + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for research artifact review. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on research artifact review. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/research-artifact-review/agents/openai.yaml b/skills/research-artifact-review/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d88c9fb624deed8009ba1bc987c3668677dce3e7 --- /dev/null +++ b/skills/research-artifact-review/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Research Artifact Review" +short_description: "Work on research artifact review for Research And Scientific AI." +default_prompt: "Use this skill to help with research artifact review in Research And Scientific AI." diff --git a/skills/research-code-packaging/SKILL.md b/skills/research-code-packaging/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..48ecfa7f34fc26bf7e2f104ab4f7d192d84a37e6 --- /dev/null +++ b/skills/research-code-packaging/SKILL.md @@ -0,0 +1,29 @@ +--- +name: research-code-packaging +description: "Guidance for research code packaging in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving research code packaging, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Research Code Packaging + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for research code packaging. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on research code packaging. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/research-code-packaging/agents/openai.yaml b/skills/research-code-packaging/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..90de0b6a9381f6c1ddc2b82fa0d12aadbdb8949c --- /dev/null +++ b/skills/research-code-packaging/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Research Code Packaging" +short_description: "Work on research code packaging for Research And Scientific AI." +default_prompt: "Use this skill to help with research code packaging in Research And Scientific AI." diff --git a/skills/response-quality-debugging/SKILL.md b/skills/response-quality-debugging/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..5460dc39a5d5c8fb34144a17ff8d01de0809a8e5 --- /dev/null +++ b/skills/response-quality-debugging/SKILL.md @@ -0,0 +1,29 @@ +--- +name: response-quality-debugging +description: "Guidance for response quality debugging in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving response quality debugging, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Response Quality Debugging + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for response quality debugging. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on response quality debugging. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/response-quality-debugging/agents/openai.yaml b/skills/response-quality-debugging/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..4a5eb87e5dac4990b62a27d873296ea364ad8f1d --- /dev/null +++ b/skills/response-quality-debugging/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Response Quality Debugging" +short_description: "Work on response quality debugging for LLM Engineering." +default_prompt: "Use this skill to help with response quality debugging in LLM Engineering." diff --git a/skills/responsive-tablet-layouts/SKILL.md b/skills/responsive-tablet-layouts/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..1c959e555559d78b95284076d84303cec9b9e4b8 --- /dev/null +++ b/skills/responsive-tablet-layouts/SKILL.md @@ -0,0 +1,29 @@ +--- +name: responsive-tablet-layouts +description: "Guidance for responsive tablet layouts in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving responsive tablet layouts, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Responsive Tablet Layouts + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for responsive tablet layouts. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on responsive tablet layouts. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/responsive-tablet-layouts/agents/openai.yaml b/skills/responsive-tablet-layouts/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7c0ab310baa335b7c416e94dbdba51f31a78ebbb --- /dev/null +++ b/skills/responsive-tablet-layouts/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Responsive Tablet Layouts" +short_description: "Work on responsive tablet layouts for Mobile App Engineering." +default_prompt: "Use this skill to help with responsive tablet layouts in Mobile App Engineering." diff --git a/skills/responsive-ui-systems/SKILL.md b/skills/responsive-ui-systems/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..56dd2c098615b3fcaa10e8d969b7f96cadec033b --- /dev/null +++ b/skills/responsive-ui-systems/SKILL.md @@ -0,0 +1,29 @@ +--- +name: responsive-ui-systems +description: "Guidance for responsive UI systems in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving responsive UI systems, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Responsive UI Systems + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for responsive UI systems. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on responsive UI systems. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/responsive-ui-systems/agents/openai.yaml b/skills/responsive-ui-systems/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e5c53791f1c325e28daf7b0dc0bd1e17bc1fa948 --- /dev/null +++ b/skills/responsive-ui-systems/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Responsive UI Systems" +short_description: "Work on responsive UI systems for Web Engineering." +default_prompt: "Use this skill to help with responsive UI systems in Web Engineering." diff --git a/skills/retail-ai-workflows/SKILL.md b/skills/retail-ai-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..9841e5ee3e8480645faaef3d332cf4d546f713ae --- /dev/null +++ b/skills/retail-ai-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: retail-ai-workflows +description: "Guidance for retail AI workflows in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving retail AI workflows, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Retail AI Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for retail AI workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on retail AI workflows. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/retail-ai-workflows/agents/openai.yaml b/skills/retail-ai-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..f9ef14d496909ce855ee9329cd1f642dacafceb5 --- /dev/null +++ b/skills/retail-ai-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Retail AI Workflows" +short_description: "Work on retail AI workflows for Domain AI." +default_prompt: "Use this skill to help with retail AI workflows in Domain AI." diff --git a/skills/retention-analysis/SKILL.md b/skills/retention-analysis/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..d983ab359a7e6b383da0efb7bfcbb23beb4a20e6 --- /dev/null +++ b/skills/retention-analysis/SKILL.md @@ -0,0 +1,29 @@ +--- +name: retention-analysis +description: "Guidance for retention analysis in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving retention analysis, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# Retention Analysis + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for retention analysis. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on retention analysis. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/retention-analysis/agents/openai.yaml b/skills/retention-analysis/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..17d5442b998d6590fd388aa41cbe7d8116395531 --- /dev/null +++ b/skills/retention-analysis/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Retention Analysis" +short_description: "Work on retention analysis for Databases And Analytics." +default_prompt: "Use this skill to help with retention analysis in Databases And Analytics." diff --git a/skills/retrieval-augmented-generation/SKILL.md b/skills/retrieval-augmented-generation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..c5eb70071a04d0b8aa47adb5e479bf0109c3f41b --- /dev/null +++ b/skills/retrieval-augmented-generation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: retrieval-augmented-generation +description: "Guidance for retrieval augmented generation in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving retrieval augmented generation, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Retrieval Augmented Generation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for retrieval augmented generation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on retrieval augmented generation. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/retrieval-augmented-generation/agents/openai.yaml b/skills/retrieval-augmented-generation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..eb22bfd836291d59d56e47739542ee364d5abed1 --- /dev/null +++ b/skills/retrieval-augmented-generation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Retrieval Augmented Generation" +short_description: "Work on retrieval augmented generation for LLM Engineering." +default_prompt: "Use this skill to help with retrieval augmented generation in LLM Engineering." diff --git a/skills/rnn-sequence-models/SKILL.md b/skills/rnn-sequence-models/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..318fa9e161f804dd97b51b5bfc65d752ce8bd17a --- /dev/null +++ b/skills/rnn-sequence-models/SKILL.md @@ -0,0 +1,29 @@ +--- +name: rnn-sequence-models +description: "Guidance for RNN sequence models in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving RNN sequence models, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# RNN Sequence Models + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for RNN sequence models. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on RNN sequence models. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/rnn-sequence-models/agents/openai.yaml b/skills/rnn-sequence-models/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..c81a509c8df8b67f4726ff2f1067c8a1a092e235 --- /dev/null +++ b/skills/rnn-sequence-models/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "RNN Sequence Models" +short_description: "Work on RNN sequence models for Deep Learning." +default_prompt: "Use this skill to help with RNN sequence models in Deep Learning." diff --git a/skills/robot-motion-planning/SKILL.md b/skills/robot-motion-planning/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..3e56a879bc50b3bf86263a740bfa2d743a4b7261 --- /dev/null +++ b/skills/robot-motion-planning/SKILL.md @@ -0,0 +1,29 @@ +--- +name: robot-motion-planning +description: "Guidance for robot motion planning in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving robot motion planning, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# Robot Motion Planning + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for robot motion planning. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on robot motion planning. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/robot-motion-planning/agents/openai.yaml b/skills/robot-motion-planning/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..1cf694c3f322abde7a8aee878fa3cfdede6675c2 --- /dev/null +++ b/skills/robot-motion-planning/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Robot Motion Planning" +short_description: "Work on robot motion planning for Robotics And IoT." +default_prompt: "Use this skill to help with robot motion planning in Robotics And IoT." diff --git a/skills/robot-perception-language/SKILL.md b/skills/robot-perception-language/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..5a5c31f665ceb41c6ef3c6f148dc35ff9ad43d6b --- /dev/null +++ b/skills/robot-perception-language/SKILL.md @@ -0,0 +1,29 @@ +--- +name: robot-perception-language +description: "Guidance for robot perception language in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving robot perception language, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Robot Perception Language + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for robot perception language. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on robot perception language. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/robot-perception-language/agents/openai.yaml b/skills/robot-perception-language/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..cc3ffaf5408f0b40766cd2960e355f6ca02e4927 --- /dev/null +++ b/skills/robot-perception-language/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Robot Perception Language" +short_description: "Work on robot perception language for Multimodal AI." +default_prompt: "Use this skill to help with robot perception language in Multimodal AI." diff --git a/skills/robot-perception/SKILL.md b/skills/robot-perception/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..f6cb98c4d9a0a13f8bbea43f18d55faa66a9e4a5 --- /dev/null +++ b/skills/robot-perception/SKILL.md @@ -0,0 +1,29 @@ +--- +name: robot-perception +description: "Guidance for robot perception in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving robot perception, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# Robot Perception + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for robot perception. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on robot perception. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/robot-perception/agents/openai.yaml b/skills/robot-perception/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b92f2a540d93801133f8f527d1d52b103f2b82ea --- /dev/null +++ b/skills/robot-perception/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Robot Perception" +short_description: "Work on robot perception for Robotics And IoT." +default_prompt: "Use this skill to help with robot perception in Robotics And IoT." diff --git a/skills/robot-simulation/SKILL.md b/skills/robot-simulation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..7d0f61a89ab8fc4c22e18fd36c61af3ae3873ecc --- /dev/null +++ b/skills/robot-simulation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: robot-simulation +description: "Guidance for robot simulation in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving robot simulation, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# Robot Simulation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for robot simulation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on robot simulation. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/robot-simulation/agents/openai.yaml b/skills/robot-simulation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..6b84184d0c1173ee3d07d71ce4fe93ac5ac706e0 --- /dev/null +++ b/skills/robot-simulation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Robot Simulation" +short_description: "Work on robot simulation for Robotics And IoT." +default_prompt: "Use this skill to help with robot simulation in Robotics And IoT." diff --git a/skills/role-prompt-hardening/SKILL.md b/skills/role-prompt-hardening/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..520566d48029503eb4becfc054403bb883d9c5c1 --- /dev/null +++ b/skills/role-prompt-hardening/SKILL.md @@ -0,0 +1,29 @@ +--- +name: role-prompt-hardening +description: "Guidance for role prompt hardening in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving role prompt hardening, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# Role Prompt Hardening + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for role prompt hardening. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on role prompt hardening. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/role-prompt-hardening/agents/openai.yaml b/skills/role-prompt-hardening/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..996f306bfeea6487de16387f04daa96ecfd0faac --- /dev/null +++ b/skills/role-prompt-hardening/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Role Prompt Hardening" +short_description: "Work on role prompt hardening for Prompting And Evaluation." +default_prompt: "Use this skill to help with role prompt hardening in Prompting And Evaluation." diff --git a/skills/rollback-plans/SKILL.md b/skills/rollback-plans/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..3b291311c83aabb599d3523de65cff1dd692c0be --- /dev/null +++ b/skills/rollback-plans/SKILL.md @@ -0,0 +1,29 @@ +--- +name: rollback-plans +description: "Guidance for rollback plans in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving rollback plans, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# Rollback Plans + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for rollback plans. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on rollback plans. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/rollback-plans/agents/openai.yaml b/skills/rollback-plans/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..690c0b9655b372cd02af466738229ae17e45ec24 --- /dev/null +++ b/skills/rollback-plans/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Rollback Plans" +short_description: "Work on rollback plans for MLOps." +default_prompt: "Use this skill to help with rollback plans in MLOps." diff --git a/skills/ros-integration/SKILL.md b/skills/ros-integration/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..68f3e084700440f7b31b38064f4a59616f5cc3c9 --- /dev/null +++ b/skills/ros-integration/SKILL.md @@ -0,0 +1,29 @@ +--- +name: ros-integration +description: "Guidance for ROS integration in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving ROS integration, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# ROS Integration + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for ROS integration. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on ROS integration. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/ros-integration/agents/openai.yaml b/skills/ros-integration/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..6abfc05b029e0291acf12948493661c86de1b7ba --- /dev/null +++ b/skills/ros-integration/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "ROS Integration" +short_description: "Work on ROS integration for Robotics And IoT." +default_prompt: "Use this skill to help with ROS integration in Robotics And IoT." diff --git a/skills/rubric-based-grading/SKILL.md b/skills/rubric-based-grading/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..323c5c0fd8ba9ccfb3bfa5dcfcf5e1879545a793 --- /dev/null +++ b/skills/rubric-based-grading/SKILL.md @@ -0,0 +1,29 @@ +--- +name: rubric-based-grading +description: "Guidance for rubric based grading in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving rubric based grading, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# Rubric Based Grading + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for rubric based grading. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on rubric based grading. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/rubric-based-grading/agents/openai.yaml b/skills/rubric-based-grading/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..cf1a089a24eb00847998cb0ba598a5761a030bab --- /dev/null +++ b/skills/rubric-based-grading/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Rubric Based Grading" +short_description: "Work on rubric based grading for Prompting And Evaluation." +default_prompt: "Use this skill to help with rubric based grading in Prompting And Evaluation." diff --git a/skills/safety-interlocks/SKILL.md b/skills/safety-interlocks/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..c5cefce86e60c0d56fe543002d73e8e8202460c3 --- /dev/null +++ b/skills/safety-interlocks/SKILL.md @@ -0,0 +1,29 @@ +--- +name: safety-interlocks +description: "Guidance for safety interlocks in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving safety interlocks, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# Safety Interlocks + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for safety interlocks. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on safety interlocks. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/safety-interlocks/agents/openai.yaml b/skills/safety-interlocks/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..2695fcf9867090732b1cbf030c26499ba44f0d87 --- /dev/null +++ b/skills/safety-interlocks/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Safety Interlocks" +short_description: "Work on safety interlocks for Robotics And IoT." +default_prompt: "Use this skill to help with safety interlocks in Robotics And IoT." diff --git a/skills/safety-refusal-handling/SKILL.md b/skills/safety-refusal-handling/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..4fe63341b681cb7aa6ec172c5ad9eb4e7f3a7c7c --- /dev/null +++ b/skills/safety-refusal-handling/SKILL.md @@ -0,0 +1,29 @@ +--- +name: safety-refusal-handling +description: "Guidance for safety refusal handling in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving safety refusal handling, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Safety Refusal Handling + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for safety refusal handling. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on safety refusal handling. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/safety-refusal-handling/agents/openai.yaml b/skills/safety-refusal-handling/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..5d78e37d0c8aaf2aaab392e2c42fd997da07287a --- /dev/null +++ b/skills/safety-refusal-handling/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Safety Refusal Handling" +short_description: "Work on safety refusal handling for LLM Engineering." +default_prompt: "Use this skill to help with safety refusal handling in LLM Engineering." diff --git a/skills/sales-ai-workflows/SKILL.md b/skills/sales-ai-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..b12bfff0c06c835b5aa2565fea1c04fd29b328f6 --- /dev/null +++ b/skills/sales-ai-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: sales-ai-workflows +description: "Guidance for sales AI workflows in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving sales AI workflows, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Sales AI Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for sales AI workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on sales AI workflows. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/sales-ai-workflows/agents/openai.yaml b/skills/sales-ai-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..6f7946ed6adcb4cd439aa23a9b2180965103eff5 --- /dev/null +++ b/skills/sales-ai-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Sales AI Workflows" +short_description: "Work on sales AI workflows for Domain AI." +default_prompt: "Use this skill to help with sales AI workflows in Domain AI." diff --git a/skills/sandboxed-execution/SKILL.md b/skills/sandboxed-execution/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a2d49b69e41ccd1fd411478e3d527115358e8c5d --- /dev/null +++ b/skills/sandboxed-execution/SKILL.md @@ -0,0 +1,29 @@ +--- +name: sandboxed-execution +description: "Guidance for sandboxed execution in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving sandboxed execution, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# Sandboxed Execution + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for sandboxed execution. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on sandboxed execution. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/sandboxed-execution/agents/openai.yaml b/skills/sandboxed-execution/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d42a5b932a2b7f5c5c7681f0de28adf24f751143 --- /dev/null +++ b/skills/sandboxed-execution/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Sandboxed Execution" +short_description: "Work on sandboxed execution for Security And Privacy." +default_prompt: "Use this skill to help with sandboxed execution in Security And Privacy." diff --git a/skills/satellite-imagery/SKILL.md b/skills/satellite-imagery/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a5f046771c05c36a3a6c2c9ffc63fb9f0eff3ac1 --- /dev/null +++ b/skills/satellite-imagery/SKILL.md @@ -0,0 +1,29 @@ +--- +name: satellite-imagery +description: "Guidance for satellite imagery in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving satellite imagery, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Satellite Imagery + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for satellite imagery. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on satellite imagery. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/satellite-imagery/agents/openai.yaml b/skills/satellite-imagery/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..5eb19be9a0ff646d4cbc38b9cc72299de40089a5 --- /dev/null +++ b/skills/satellite-imagery/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Satellite Imagery" +short_description: "Work on satellite imagery for Computer Vision." +default_prompt: "Use this skill to help with satellite imagery in Computer Vision." diff --git a/skills/schema-evolution/SKILL.md b/skills/schema-evolution/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..c79601303f6a009461f7832b4219226fcd03cdef --- /dev/null +++ b/skills/schema-evolution/SKILL.md @@ -0,0 +1,29 @@ +--- +name: schema-evolution +description: "Guidance for schema evolution in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving schema evolution, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Schema Evolution + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for schema evolution. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on schema evolution. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/schema-evolution/agents/openai.yaml b/skills/schema-evolution/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..6b03be643841f0bae710fdeee943e59ef28d8bcc --- /dev/null +++ b/skills/schema-evolution/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Schema Evolution" +short_description: "Work on schema evolution for Data Engineering." +default_prompt: "Use this skill to help with schema evolution in Data Engineering." diff --git a/skills/scientific-literature-ai/SKILL.md b/skills/scientific-literature-ai/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..55474d49e5191083bc4f7a81344640366c0d1dd6 --- /dev/null +++ b/skills/scientific-literature-ai/SKILL.md @@ -0,0 +1,29 @@ +--- +name: scientific-literature-ai +description: "Guidance for scientific literature AI in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving scientific literature AI, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Scientific Literature AI + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for scientific literature AI. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on scientific literature AI. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/scientific-literature-ai/agents/openai.yaml b/skills/scientific-literature-ai/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3df0bc3b883e014d680452fbb3ccc0e9a67cf068 --- /dev/null +++ b/skills/scientific-literature-ai/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Scientific Literature AI" +short_description: "Work on scientific literature AI for Domain AI." +default_prompt: "Use this skill to help with scientific literature AI in Domain AI." diff --git a/skills/scientific-visualization/SKILL.md b/skills/scientific-visualization/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..ad119097ae1f49301fe15b980d2ec642945672b8 --- /dev/null +++ b/skills/scientific-visualization/SKILL.md @@ -0,0 +1,29 @@ +--- +name: scientific-visualization +description: "Guidance for scientific visualization in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving scientific visualization, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Scientific Visualization + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for scientific visualization. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on scientific visualization. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/scientific-visualization/agents/openai.yaml b/skills/scientific-visualization/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..95a457bc161b406a7af5278ea65a4c6b9f0c457b --- /dev/null +++ b/skills/scientific-visualization/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Scientific Visualization" +short_description: "Work on scientific visualization for Research And Scientific AI." +default_prompt: "Use this skill to help with scientific visualization in Research And Scientific AI." diff --git a/skills/screen-understanding/SKILL.md b/skills/screen-understanding/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..4e5d0cde04c5aed076f072f7897b974272896baa --- /dev/null +++ b/skills/screen-understanding/SKILL.md @@ -0,0 +1,29 @@ +--- +name: screen-understanding +description: "Guidance for screen understanding in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving screen understanding, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Screen Understanding + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for screen understanding. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on screen understanding. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/screen-understanding/agents/openai.yaml b/skills/screen-understanding/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3c2d2ff96e7c0e14d794ef51af283f9897414969 --- /dev/null +++ b/skills/screen-understanding/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Screen Understanding" +short_description: "Work on screen understanding for Multimodal AI." +default_prompt: "Use this skill to help with screen understanding in Multimodal AI." diff --git a/skills/search-assistant-ux/SKILL.md b/skills/search-assistant-ux/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..40672de35c8a266d606aa1928dd96aa6ffc8da6a --- /dev/null +++ b/skills/search-assistant-ux/SKILL.md @@ -0,0 +1,29 @@ +--- +name: search-assistant-ux +description: "Guidance for search assistant UX in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving search assistant UX, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# Search Assistant UX + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for search assistant UX. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on search assistant UX. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/search-assistant-ux/agents/openai.yaml b/skills/search-assistant-ux/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..8be59f59e138272c89688385d5a51ce683095ed0 --- /dev/null +++ b/skills/search-assistant-ux/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Search Assistant UX" +short_description: "Work on search assistant UX for AI Product And UX." +default_prompt: "Use this skill to help with search assistant UX in AI Product And UX." diff --git a/skills/secret-scanning/SKILL.md b/skills/secret-scanning/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..b97f74de5634fd34b7c8a62a6492f60385ac9455 --- /dev/null +++ b/skills/secret-scanning/SKILL.md @@ -0,0 +1,29 @@ +--- +name: secret-scanning +description: "Guidance for secret scanning in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving secret scanning, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# Secret Scanning + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for secret scanning. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on secret scanning. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/secret-scanning/agents/openai.yaml b/skills/secret-scanning/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e3aa71588e488bd93fad3d31eb52340333ce99c2 --- /dev/null +++ b/skills/secret-scanning/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Secret Scanning" +short_description: "Work on secret scanning for Security And Privacy." +default_prompt: "Use this skill to help with secret scanning in Security And Privacy." diff --git a/skills/secrets-management/SKILL.md b/skills/secrets-management/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..ac26e25d84b14245a15293ecb81bce98d7774c34 --- /dev/null +++ b/skills/secrets-management/SKILL.md @@ -0,0 +1,29 @@ +--- +name: secrets-management +description: "Guidance for secrets management in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving secrets management, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# Secrets Management + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for secrets management. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on secrets management. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/secrets-management/agents/openai.yaml b/skills/secrets-management/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..fcf7abaec5e0afb8e4674b199c3fac015e9972b2 --- /dev/null +++ b/skills/secrets-management/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Secrets Management" +short_description: "Work on secrets management for Cloud And DevOps." +default_prompt: "Use this skill to help with secrets management in Cloud And DevOps." diff --git a/skills/secure-code-review/SKILL.md b/skills/secure-code-review/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..85f1504a76f41e3406ac9586a4a2fbe3224531b5 --- /dev/null +++ b/skills/secure-code-review/SKILL.md @@ -0,0 +1,29 @@ +--- +name: secure-code-review +description: "Guidance for secure code review in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving secure code review, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# Secure Code Review + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for secure code review. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on secure code review. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/secure-code-review/agents/openai.yaml b/skills/secure-code-review/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..67377f5c873e4d930ba168a36c231d7a21df0d25 --- /dev/null +++ b/skills/secure-code-review/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Secure Code Review" +short_description: "Work on secure code review for Security And Privacy." +default_prompt: "Use this skill to help with secure code review in Security And Privacy." diff --git a/skills/secure-local-storage/SKILL.md b/skills/secure-local-storage/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..8ce35b684e564ac392affb36b9c2c7123b8eb047 --- /dev/null +++ b/skills/secure-local-storage/SKILL.md @@ -0,0 +1,29 @@ +--- +name: secure-local-storage +description: "Guidance for secure local storage in Mobile App Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving secure local storage, mobile app engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Secure Local Storage + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for secure local storage. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Mobile App Engineering task centered on secure local storage. +- Design for offline, permissions, device sizes, and release stores. +- Test on realistic devices or emulators. +- Protect local data and background tasks deliberately. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/secure-local-storage/agents/openai.yaml b/skills/secure-local-storage/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..6dcbae0c2366ff4d4d5900786728fc6b2f8fa162 --- /dev/null +++ b/skills/secure-local-storage/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Secure Local Storage" +short_description: "Work on secure local storage for Mobile App Engineering." +default_prompt: "Use this skill to help with secure local storage in Mobile App Engineering." diff --git a/skills/security-monitoring/SKILL.md b/skills/security-monitoring/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a4bb7fb438e740098c668b7658873bedfd5d0cc3 --- /dev/null +++ b/skills/security-monitoring/SKILL.md @@ -0,0 +1,29 @@ +--- +name: security-monitoring +description: "Guidance for security monitoring in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving security monitoring, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# Security Monitoring + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for security monitoring. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on security monitoring. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/security-monitoring/agents/openai.yaml b/skills/security-monitoring/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ec0687ac3d14a302178d74e6283e4b609fee43ce --- /dev/null +++ b/skills/security-monitoring/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Security Monitoring" +short_description: "Work on security monitoring for Security And Privacy." +default_prompt: "Use this skill to help with security monitoring in Security And Privacy." diff --git a/skills/self-supervised-learning/SKILL.md b/skills/self-supervised-learning/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..b62ded76bed925428dffb43a1f4c1525518c6049 --- /dev/null +++ b/skills/self-supervised-learning/SKILL.md @@ -0,0 +1,29 @@ +--- +name: self-supervised-learning +description: "Guidance for self supervised learning in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving self supervised learning, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Self Supervised Learning + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for self supervised learning. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on self supervised learning. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/self-supervised-learning/agents/openai.yaml b/skills/self-supervised-learning/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e989b6359f7dbdc923176ae1094877caa51d2f01 --- /dev/null +++ b/skills/self-supervised-learning/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Self Supervised Learning" +short_description: "Work on self supervised learning for Deep Learning." +default_prompt: "Use this skill to help with self supervised learning in Deep Learning." diff --git a/skills/semantic-cache-design/SKILL.md b/skills/semantic-cache-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..656b5ed60fe814d2b7cccbaa72488baf3e300167 --- /dev/null +++ b/skills/semantic-cache-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: semantic-cache-design +description: "Guidance for semantic cache design in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving semantic cache design, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Semantic Cache Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for semantic cache design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on semantic cache design. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/semantic-cache-design/agents/openai.yaml b/skills/semantic-cache-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..43a9ea7427ce145becfedf57274f18154aaf9064 --- /dev/null +++ b/skills/semantic-cache-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Semantic Cache Design" +short_description: "Work on semantic cache design for LLM Engineering." +default_prompt: "Use this skill to help with semantic cache design in LLM Engineering." diff --git a/skills/semantic-search/SKILL.md b/skills/semantic-search/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..317f14b044dab7110ae4cf475ac968c0d674140a --- /dev/null +++ b/skills/semantic-search/SKILL.md @@ -0,0 +1,29 @@ +--- +name: semantic-search +description: "Guidance for semantic search in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving semantic search, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Semantic Search + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for semantic search. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on semantic search. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/semantic-search/agents/openai.yaml b/skills/semantic-search/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..26f7e56e4875f4f3a9ce494b12fff91902807119 --- /dev/null +++ b/skills/semantic-search/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Semantic Search" +short_description: "Work on semantic search for Natural Language Processing." +default_prompt: "Use this skill to help with semantic search in Natural Language Processing." diff --git a/skills/semantic-segmentation/SKILL.md b/skills/semantic-segmentation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..62c1c2deff79868801ecc832f59316248decfd98 --- /dev/null +++ b/skills/semantic-segmentation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: semantic-segmentation +description: "Guidance for semantic segmentation in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving semantic segmentation, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Semantic Segmentation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for semantic segmentation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on semantic segmentation. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/semantic-segmentation/agents/openai.yaml b/skills/semantic-segmentation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..428f87b673c8254df253c85342040fbc881924f0 --- /dev/null +++ b/skills/semantic-segmentation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Semantic Segmentation" +short_description: "Work on semantic segmentation for Computer Vision." +default_prompt: "Use this skill to help with semantic segmentation in Computer Vision." diff --git a/skills/semi-supervised-learning/SKILL.md b/skills/semi-supervised-learning/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..b645be5752b20143db319615ccf5ee985600a3ae --- /dev/null +++ b/skills/semi-supervised-learning/SKILL.md @@ -0,0 +1,29 @@ +--- +name: semi-supervised-learning +description: "Guidance for semi supervised learning in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving semi supervised learning, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Semi Supervised Learning + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for semi supervised learning. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on semi supervised learning. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/semi-supervised-learning/agents/openai.yaml b/skills/semi-supervised-learning/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..c0c5d725be76dbbf0f2fdfd793218b17f2f66b7e --- /dev/null +++ b/skills/semi-supervised-learning/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Semi Supervised Learning" +short_description: "Work on semi supervised learning for Machine Learning." +default_prompt: "Use this skill to help with semi supervised learning in Machine Learning." diff --git a/skills/sensor-fusion/SKILL.md b/skills/sensor-fusion/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..468823170df710611146deeb0791a8ffb3f0242d --- /dev/null +++ b/skills/sensor-fusion/SKILL.md @@ -0,0 +1,29 @@ +--- +name: sensor-fusion +description: "Guidance for sensor fusion in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving sensor fusion, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# Sensor Fusion + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for sensor fusion. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on sensor fusion. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/sensor-fusion/agents/openai.yaml b/skills/sensor-fusion/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..765d5e31a9ed6edbd1fe8bcd55ed330820b237a1 --- /dev/null +++ b/skills/sensor-fusion/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Sensor Fusion" +short_description: "Work on sensor fusion for Robotics And IoT." +default_prompt: "Use this skill to help with sensor fusion in Robotics And IoT." diff --git a/skills/sentiment-analysis/SKILL.md b/skills/sentiment-analysis/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..b2ae65e2b1d45b58ca93fd5845ee2280729d3143 --- /dev/null +++ b/skills/sentiment-analysis/SKILL.md @@ -0,0 +1,29 @@ +--- +name: sentiment-analysis +description: "Guidance for sentiment analysis in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving sentiment analysis, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Sentiment Analysis + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for sentiment analysis. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on sentiment analysis. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/sentiment-analysis/agents/openai.yaml b/skills/sentiment-analysis/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..38ce6f52ad8e1fb24eb3d518d4d5ebab7d3ee3ae --- /dev/null +++ b/skills/sentiment-analysis/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Sentiment Analysis" +short_description: "Work on sentiment analysis for Natural Language Processing." +default_prompt: "Use this skill to help with sentiment analysis in Natural Language Processing." diff --git a/skills/seo-technical-checks/SKILL.md b/skills/seo-technical-checks/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..772578b942d1d6e03c630c37e2f45e66986fb522 --- /dev/null +++ b/skills/seo-technical-checks/SKILL.md @@ -0,0 +1,29 @@ +--- +name: seo-technical-checks +description: "Guidance for SEO technical checks in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving SEO technical checks, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# SEO Technical Checks + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for SEO technical checks. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on SEO technical checks. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/seo-technical-checks/agents/openai.yaml b/skills/seo-technical-checks/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..91b740b994e7f29bc0dcf02836bbd75414c8bce8 --- /dev/null +++ b/skills/seo-technical-checks/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "SEO Technical Checks" +short_description: "Work on SEO technical checks for Web Engineering." +default_prompt: "Use this skill to help with SEO technical checks in Web Engineering." diff --git a/skills/server-side-rendering/SKILL.md b/skills/server-side-rendering/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..49801cf2b8a112844336f30636e4008abf855c71 --- /dev/null +++ b/skills/server-side-rendering/SKILL.md @@ -0,0 +1,29 @@ +--- +name: server-side-rendering +description: "Guidance for server side rendering in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving server side rendering, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Server Side Rendering + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for server side rendering. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on server side rendering. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/server-side-rendering/agents/openai.yaml b/skills/server-side-rendering/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b7706bc9820544d54dee723e0f8fe62197e18c58 --- /dev/null +++ b/skills/server-side-rendering/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Server Side Rendering" +short_description: "Work on server side rendering for Web Engineering." +default_prompt: "Use this skill to help with server side rendering in Web Engineering." diff --git a/skills/serverless-functions/SKILL.md b/skills/serverless-functions/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..6e364a618ee093bef3bb561549e56b7218c69500 --- /dev/null +++ b/skills/serverless-functions/SKILL.md @@ -0,0 +1,29 @@ +--- +name: serverless-functions +description: "Guidance for serverless functions in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving serverless functions, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# Serverless Functions + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for serverless functions. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on serverless functions. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/serverless-functions/agents/openai.yaml b/skills/serverless-functions/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..00f6a4a82258f2927df0b54e078348eb1550adee --- /dev/null +++ b/skills/serverless-functions/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Serverless Functions" +short_description: "Work on serverless functions for Cloud And DevOps." +default_prompt: "Use this skill to help with serverless functions in Cloud And DevOps." diff --git a/skills/shadow-deployments/SKILL.md b/skills/shadow-deployments/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..bfb3202e6dfadfbed61bcd51c22fdf5e151ea51b --- /dev/null +++ b/skills/shadow-deployments/SKILL.md @@ -0,0 +1,29 @@ +--- +name: shadow-deployments +description: "Guidance for shadow deployments in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving shadow deployments, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# Shadow Deployments + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for shadow deployments. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on shadow deployments. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/shadow-deployments/agents/openai.yaml b/skills/shadow-deployments/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..4fd0f1964c38f4aabb0cec67fedd92c39bcbedeb --- /dev/null +++ b/skills/shadow-deployments/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Shadow Deployments" +short_description: "Work on shadow deployments for MLOps." +default_prompt: "Use this skill to help with shadow deployments in MLOps." diff --git a/skills/simulation-surrogate-models/SKILL.md b/skills/simulation-surrogate-models/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..88cd4307468ad8aab269de80fa10ec5333f1fa4f --- /dev/null +++ b/skills/simulation-surrogate-models/SKILL.md @@ -0,0 +1,29 @@ +--- +name: simulation-surrogate-models +description: "Guidance for simulation surrogate models in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving simulation surrogate models, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Simulation Surrogate Models + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for simulation surrogate models. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on simulation surrogate models. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/simulation-surrogate-models/agents/openai.yaml b/skills/simulation-surrogate-models/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..a373f0aa92572aa9616d8ecb10ea4cbe2e7b2dd8 --- /dev/null +++ b/skills/simulation-surrogate-models/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Simulation Surrogate Models" +short_description: "Work on simulation surrogate models for Research And Scientific AI." +default_prompt: "Use this skill to help with simulation surrogate models in Research And Scientific AI." diff --git a/skills/slam-workflows/SKILL.md b/skills/slam-workflows/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..14ac5dec90ef6f8d51d0681d1873f6551f144756 --- /dev/null +++ b/skills/slam-workflows/SKILL.md @@ -0,0 +1,29 @@ +--- +name: slam-workflows +description: "Guidance for SLAM workflows in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving SLAM workflows, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# SLAM Workflows + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for SLAM workflows. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on SLAM workflows. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/slam-workflows/agents/openai.yaml b/skills/slam-workflows/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b19ca09161ca686c13810f9136bedf3b15ded0c2 --- /dev/null +++ b/skills/slam-workflows/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "SLAM Workflows" +short_description: "Work on SLAM workflows for Robotics And IoT." +default_prompt: "Use this skill to help with SLAM workflows in Robotics And IoT." diff --git a/skills/slot-filling/SKILL.md b/skills/slot-filling/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..5a02f9385408fb487c118760294ded8475254f16 --- /dev/null +++ b/skills/slot-filling/SKILL.md @@ -0,0 +1,29 @@ +--- +name: slot-filling +description: "Guidance for slot filling in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving slot filling, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Slot Filling + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for slot filling. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on slot filling. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/slot-filling/agents/openai.yaml b/skills/slot-filling/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..475447d9c275c80f729df0a435846da496b717f3 --- /dev/null +++ b/skills/slot-filling/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Slot Filling" +short_description: "Work on slot filling for Natural Language Processing." +default_prompt: "Use this skill to help with slot filling in Natural Language Processing." diff --git a/skills/source-separation/SKILL.md b/skills/source-separation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..33e89692cee1be18b657459cbef02a2c7df0340d --- /dev/null +++ b/skills/source-separation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: source-separation +description: "Guidance for source separation in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving source separation, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Source Separation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for source separation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on source separation. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/source-separation/agents/openai.yaml b/skills/source-separation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..eeaf44630578a6746c7d907ccac03d8d41345da8 --- /dev/null +++ b/skills/source-separation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Source Separation" +short_description: "Work on source separation for Speech And Audio." +default_prompt: "Use this skill to help with source separation in Speech And Audio." diff --git a/skills/speaker-diarization/SKILL.md b/skills/speaker-diarization/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..953a4157dc71e2253a284a3bffea6c350c9d6026 --- /dev/null +++ b/skills/speaker-diarization/SKILL.md @@ -0,0 +1,29 @@ +--- +name: speaker-diarization +description: "Guidance for speaker diarization in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving speaker diarization, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Speaker Diarization + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for speaker diarization. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on speaker diarization. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/speaker-diarization/agents/openai.yaml b/skills/speaker-diarization/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..4565e440337dd99c8b8ce4cf788c6ae08f5aa812 --- /dev/null +++ b/skills/speaker-diarization/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Speaker Diarization" +short_description: "Work on speaker diarization for Speech And Audio." +default_prompt: "Use this skill to help with speaker diarization in Speech And Audio." diff --git a/skills/speaker-verification/SKILL.md b/skills/speaker-verification/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..d6862e27bf1cbde232d705cd84dad1d5980c8875 --- /dev/null +++ b/skills/speaker-verification/SKILL.md @@ -0,0 +1,29 @@ +--- +name: speaker-verification +description: "Guidance for speaker verification in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving speaker verification, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Speaker Verification + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for speaker verification. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on speaker verification. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/speaker-verification/agents/openai.yaml b/skills/speaker-verification/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..74b11b53ed3187ed0aa7ef1f2e3658b86f1dfbea --- /dev/null +++ b/skills/speaker-verification/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Speaker Verification" +short_description: "Work on speaker verification for Speech And Audio." +default_prompt: "Use this skill to help with speaker verification in Speech And Audio." diff --git a/skills/speech-evaluation/SKILL.md b/skills/speech-evaluation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..6a6073253435f660e66c988ed8b870067f446eb4 --- /dev/null +++ b/skills/speech-evaluation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: speech-evaluation +description: "Guidance for speech evaluation in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving speech evaluation, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Speech Evaluation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for speech evaluation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on speech evaluation. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/speech-evaluation/agents/openai.yaml b/skills/speech-evaluation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ddcb8d96811124197923a20de3dc063117dce06d --- /dev/null +++ b/skills/speech-evaluation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Speech Evaluation" +short_description: "Work on speech evaluation for Speech And Audio." +default_prompt: "Use this skill to help with speech evaluation in Speech And Audio." diff --git a/skills/speech-recognition/SKILL.md b/skills/speech-recognition/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..6a7321fa23472815e3241b685a85123f3f1291d8 --- /dev/null +++ b/skills/speech-recognition/SKILL.md @@ -0,0 +1,29 @@ +--- +name: speech-recognition +description: "Guidance for speech recognition in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving speech recognition, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Speech Recognition + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for speech recognition. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on speech recognition. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/speech-recognition/agents/openai.yaml b/skills/speech-recognition/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..6404a1b51a5e8e0c423e2af8f3cb4f86dfc672de --- /dev/null +++ b/skills/speech-recognition/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Speech Recognition" +short_description: "Work on speech recognition for Speech And Audio." +default_prompt: "Use this skill to help with speech recognition in Speech And Audio." diff --git a/skills/sql-injection-prevention/SKILL.md b/skills/sql-injection-prevention/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..d75a666ed0dcfc3a325b86f0e27e738ea99ec551 --- /dev/null +++ b/skills/sql-injection-prevention/SKILL.md @@ -0,0 +1,29 @@ +--- +name: sql-injection-prevention +description: "Guidance for SQL injection prevention in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving SQL injection prevention, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# SQL Injection Prevention + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for SQL injection prevention. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on SQL injection prevention. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/sql-injection-prevention/agents/openai.yaml b/skills/sql-injection-prevention/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..617537dd7d8598cb5d094df093c5e3cf297abaab --- /dev/null +++ b/skills/sql-injection-prevention/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "SQL Injection Prevention" +short_description: "Work on SQL injection prevention for Security And Privacy." +default_prompt: "Use this skill to help with SQL injection prevention in Security And Privacy." diff --git a/skills/sqlite-embedded-storage/SKILL.md b/skills/sqlite-embedded-storage/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..193d6dc7b80e6cb37d9cd130e3241244728d06f2 --- /dev/null +++ b/skills/sqlite-embedded-storage/SKILL.md @@ -0,0 +1,29 @@ +--- +name: sqlite-embedded-storage +description: "Guidance for SQLite embedded storage in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving SQLite embedded storage, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# SQLite Embedded Storage + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for SQLite embedded storage. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on SQLite embedded storage. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/sqlite-embedded-storage/agents/openai.yaml b/skills/sqlite-embedded-storage/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9c33032c85e214c2ba4ba92197d59fd5eb5e8d83 --- /dev/null +++ b/skills/sqlite-embedded-storage/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "SQLite Embedded Storage" +short_description: "Work on SQLite embedded storage for Databases And Analytics." +default_prompt: "Use this skill to help with SQLite embedded storage in Databases And Analytics." diff --git a/skills/state-machine-agents/SKILL.md b/skills/state-machine-agents/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a67abca612e9b1f03d39bb9eacf1d3063c7d42dd --- /dev/null +++ b/skills/state-machine-agents/SKILL.md @@ -0,0 +1,29 @@ +--- +name: state-machine-agents +description: "Guidance for state machine agents in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving state machine agents, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# State Machine Agents + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for state machine agents. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on state machine agents. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/state-machine-agents/agents/openai.yaml b/skills/state-machine-agents/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..c5425073fe68759d52bf574cccc5fc9e807fa375 --- /dev/null +++ b/skills/state-machine-agents/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "State Machine Agents" +short_description: "Work on state machine agents for Agentic AI." +default_prompt: "Use this skill to help with state machine agents in Agentic AI." diff --git a/skills/state-management/SKILL.md b/skills/state-management/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..0a610854ad1aff424d6291d6cb002bb66128611b --- /dev/null +++ b/skills/state-management/SKILL.md @@ -0,0 +1,29 @@ +--- +name: state-management +description: "Guidance for state management in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving state management, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# State Management + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for state management. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on state management. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/state-management/agents/openai.yaml b/skills/state-management/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..a8e24c8513380a86f699a1f0cfd886d854ab66ed --- /dev/null +++ b/skills/state-management/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "State Management" +short_description: "Work on state management for Web Engineering." +default_prompt: "Use this skill to help with state management in Web Engineering." diff --git a/skills/static-site-generation/SKILL.md b/skills/static-site-generation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..d5d07860abafd8b28560231288cd9bcf5207b08f --- /dev/null +++ b/skills/static-site-generation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: static-site-generation +description: "Guidance for static site generation in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving static site generation, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Static Site Generation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for static site generation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on static site generation. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/static-site-generation/agents/openai.yaml b/skills/static-site-generation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..59d3fc958c5f2864ca8902a4241d2574933ccce7 --- /dev/null +++ b/skills/static-site-generation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Static Site Generation" +short_description: "Work on static site generation for Web Engineering." +default_prompt: "Use this skill to help with static site generation in Web Engineering." diff --git a/skills/statistical-significance-testing/SKILL.md b/skills/statistical-significance-testing/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..74db0b5688d3c982bc6a71a4a6ca2e52c54e4b30 --- /dev/null +++ b/skills/statistical-significance-testing/SKILL.md @@ -0,0 +1,29 @@ +--- +name: statistical-significance-testing +description: "Guidance for statistical significance testing in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving statistical significance testing, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Statistical Significance Testing + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for statistical significance testing. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on statistical significance testing. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/statistical-significance-testing/agents/openai.yaml b/skills/statistical-significance-testing/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..db4350086dd98475c50e60c7af63fe1b0dacb2cb --- /dev/null +++ b/skills/statistical-significance-testing/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Statistical Significance Testing" +short_description: "Work on statistical significance testing for Research And Scientific AI." +default_prompt: "Use this skill to help with statistical significance testing in Research And Scientific AI." diff --git a/skills/stereo-vision/SKILL.md b/skills/stereo-vision/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..88bc75aae4ab14ba5b5543fd301403cc3a4dedae --- /dev/null +++ b/skills/stereo-vision/SKILL.md @@ -0,0 +1,29 @@ +--- +name: stereo-vision +description: "Guidance for stereo vision in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving stereo vision, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Stereo Vision + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for stereo vision. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on stereo vision. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/stereo-vision/agents/openai.yaml b/skills/stereo-vision/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..1cb0f56ce86d6f9c19b1975d25cb2fa7f0a01092 --- /dev/null +++ b/skills/stereo-vision/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Stereo Vision" +short_description: "Work on stereo vision for Computer Vision." +default_prompt: "Use this skill to help with stereo vision in Computer Vision." diff --git a/skills/stream-processing/SKILL.md b/skills/stream-processing/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a45774fb385773d4483af1ebe5dcf0831928d5fb --- /dev/null +++ b/skills/stream-processing/SKILL.md @@ -0,0 +1,29 @@ +--- +name: stream-processing +description: "Guidance for stream processing in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving stream processing, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Stream Processing + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for stream processing. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on stream processing. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/stream-processing/agents/openai.yaml b/skills/stream-processing/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..dde758ef501c9a3e5925d34b12bc1aac717ab5d8 --- /dev/null +++ b/skills/stream-processing/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Stream Processing" +short_description: "Work on stream processing for Data Engineering." +default_prompt: "Use this skill to help with stream processing in Data Engineering." diff --git a/skills/streaming-response-handling/SKILL.md b/skills/streaming-response-handling/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..58e1b7aa38721c8a32fc51b8cc5e5382d8f12811 --- /dev/null +++ b/skills/streaming-response-handling/SKILL.md @@ -0,0 +1,29 @@ +--- +name: streaming-response-handling +description: "Guidance for streaming response handling in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving streaming response handling, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Streaming Response Handling + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for streaming response handling. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on streaming response handling. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/streaming-response-handling/agents/openai.yaml b/skills/streaming-response-handling/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..694367e0ab68fc6c9ca1ee591168fab5b80e6f05 --- /dev/null +++ b/skills/streaming-response-handling/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Streaming Response Handling" +short_description: "Work on streaming response handling for LLM Engineering." +default_prompt: "Use this skill to help with streaming response handling in LLM Engineering." diff --git a/skills/structured-output-schemas/SKILL.md b/skills/structured-output-schemas/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..c8eea3a09bb9c76af809d63c8e1961d5e6a8cd3e --- /dev/null +++ b/skills/structured-output-schemas/SKILL.md @@ -0,0 +1,29 @@ +--- +name: structured-output-schemas +description: "Guidance for structured output schemas in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving structured output schemas, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Structured Output Schemas + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for structured output schemas. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on structured output schemas. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/structured-output-schemas/agents/openai.yaml b/skills/structured-output-schemas/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..40a44f6da14f121a60818ca0995efc39d723325c --- /dev/null +++ b/skills/structured-output-schemas/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Structured Output Schemas" +short_description: "Work on structured output schemas for LLM Engineering." +default_prompt: "Use this skill to help with structured output schemas in LLM Engineering." diff --git a/skills/subtask-delegation/SKILL.md b/skills/subtask-delegation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..aff4a9553e15a1b32e71d97b9c518dd37427af3b --- /dev/null +++ b/skills/subtask-delegation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: subtask-delegation +description: "Guidance for subtask delegation in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving subtask delegation, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Subtask Delegation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for subtask delegation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on subtask delegation. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/subtask-delegation/agents/openai.yaml b/skills/subtask-delegation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ad328ba914436fdc58edba104c8a9903ef4f8f34 --- /dev/null +++ b/skills/subtask-delegation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Subtask Delegation" +short_description: "Work on subtask delegation for Agentic AI." +default_prompt: "Use this skill to help with subtask delegation in Agentic AI." diff --git a/skills/subtitle-generation/SKILL.md b/skills/subtitle-generation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..58d7aa57352da8443d4a9bb2802405298c8ae67e --- /dev/null +++ b/skills/subtitle-generation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: subtitle-generation +description: "Guidance for subtitle generation in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving subtitle generation, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Subtitle Generation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for subtitle generation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on subtitle generation. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/subtitle-generation/agents/openai.yaml b/skills/subtitle-generation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..6a185ac4bbd36c0bacadff58d29b955744dbf2ec --- /dev/null +++ b/skills/subtitle-generation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Subtitle Generation" +short_description: "Work on subtitle generation for Speech And Audio." +default_prompt: "Use this skill to help with subtitle generation in Speech And Audio." diff --git a/skills/summarization/SKILL.md b/skills/summarization/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..ac1d6e2ff409a048455d35b1e57a0eed4ccb645e --- /dev/null +++ b/skills/summarization/SKILL.md @@ -0,0 +1,29 @@ +--- +name: summarization +description: "Guidance for summarization in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving summarization, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Summarization + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for summarization. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on summarization. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/summarization/agents/openai.yaml b/skills/summarization/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..bd7f579846c42f322f880ca932e8376c99cee5de --- /dev/null +++ b/skills/summarization/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Summarization" +short_description: "Work on summarization for Natural Language Processing." +default_prompt: "Use this skill to help with summarization in Natural Language Processing." diff --git a/skills/supply-chain-ai/SKILL.md b/skills/supply-chain-ai/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..921ba95c988904e2fca34afc0642522e948fa244 --- /dev/null +++ b/skills/supply-chain-ai/SKILL.md @@ -0,0 +1,29 @@ +--- +name: supply-chain-ai +description: "Guidance for supply chain AI in Domain AI. Use when Codex needs to plan, build, review, test, debug, or document work involving supply chain AI, domain ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Supply Chain AI + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for supply chain AI. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Domain AI task centered on supply chain AI. +- Confirm domain regulations, workflow owners, and data sensitivity. +- Keep humans accountable for high impact decisions. +- Validate outputs with domain specific examples and review paths. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/supply-chain-ai/agents/openai.yaml b/skills/supply-chain-ai/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..99515ef259084f52bae031f4a8b204d96c7589d2 --- /dev/null +++ b/skills/supply-chain-ai/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Supply Chain AI" +short_description: "Work on supply chain AI for Domain AI." +default_prompt: "Use this skill to help with supply chain AI in Domain AI." diff --git a/skills/supply-chain-security/SKILL.md b/skills/supply-chain-security/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..eb4fe42a47058b73d693128f341d1a3e06560b32 --- /dev/null +++ b/skills/supply-chain-security/SKILL.md @@ -0,0 +1,29 @@ +--- +name: supply-chain-security +description: "Guidance for supply chain security in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving supply chain security, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# Supply Chain Security + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for supply chain security. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on supply chain security. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/supply-chain-security/agents/openai.yaml b/skills/supply-chain-security/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..66102e48cec4cf4870477f0549efc4ba2c0e0d29 --- /dev/null +++ b/skills/supply-chain-security/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Supply Chain Security" +short_description: "Work on supply chain security for Security And Privacy." +default_prompt: "Use this skill to help with supply chain security in Security And Privacy." diff --git a/skills/survival-analysis/SKILL.md b/skills/survival-analysis/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..2d53d461783c01cfff15630661ff5218fcb23e2b --- /dev/null +++ b/skills/survival-analysis/SKILL.md @@ -0,0 +1,29 @@ +--- +name: survival-analysis +description: "Guidance for survival analysis in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving survival analysis, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Survival Analysis + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for survival analysis. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on survival analysis. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/survival-analysis/agents/openai.yaml b/skills/survival-analysis/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..f93b575fa63bd16ce4c5474196682f339d0e4bab --- /dev/null +++ b/skills/survival-analysis/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Survival Analysis" +short_description: "Work on survival analysis for Machine Learning." +default_prompt: "Use this skill to help with survival analysis in Machine Learning." diff --git a/skills/svelte-application-architecture/SKILL.md b/skills/svelte-application-architecture/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..b946c26d9da01467828b84b78e512f1981372b92 --- /dev/null +++ b/skills/svelte-application-architecture/SKILL.md @@ -0,0 +1,29 @@ +--- +name: svelte-application-architecture +description: "Guidance for Svelte application architecture in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving Svelte application architecture, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Svelte Application Architecture + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for Svelte application architecture. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on Svelte application architecture. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/svelte-application-architecture/agents/openai.yaml b/skills/svelte-application-architecture/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..0cd57d4a97739d956763e9eb4a74500b0634fab1 --- /dev/null +++ b/skills/svelte-application-architecture/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Svelte Application Architecture" +short_description: "Work on Svelte application architecture for Web Engineering." +default_prompt: "Use this skill to help with Svelte application architecture in Web Engineering." diff --git a/skills/synthetic-control-studies/SKILL.md b/skills/synthetic-control-studies/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..3e3af6be10722c33ffc46a06024ce917d82b70d0 --- /dev/null +++ b/skills/synthetic-control-studies/SKILL.md @@ -0,0 +1,29 @@ +--- +name: synthetic-control-studies +description: "Guidance for synthetic control studies in Research And Scientific AI. Use when Codex needs to plan, build, review, test, debug, or document work involving synthetic control studies, research and scientific ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Synthetic Control Studies + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for synthetic control studies. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Research And Scientific AI task centered on synthetic control studies. +- Preserve provenance, seeds, configs, and environment details. +- Separate claims, experiments, and evidence. +- Package artifacts so another researcher can reproduce results. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/synthetic-control-studies/agents/openai.yaml b/skills/synthetic-control-studies/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b1b3d01cacfe885bc17e7ced97467cc4713fca75 --- /dev/null +++ b/skills/synthetic-control-studies/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Synthetic Control Studies" +short_description: "Work on synthetic control studies for Research And Scientific AI." +default_prompt: "Use this skill to help with synthetic control studies in Research And Scientific AI." diff --git a/skills/synthetic-data-generation/SKILL.md b/skills/synthetic-data-generation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..71539734f6cc3f2a308887edcea28cc485fbd057 --- /dev/null +++ b/skills/synthetic-data-generation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: synthetic-data-generation +description: "Guidance for synthetic data generation in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving synthetic data generation, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Synthetic Data Generation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for synthetic data generation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on synthetic data generation. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/synthetic-data-generation/agents/openai.yaml b/skills/synthetic-data-generation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..67be90c2d5886da0e01b7309570d85850845c23c --- /dev/null +++ b/skills/synthetic-data-generation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Synthetic Data Generation" +short_description: "Work on synthetic data generation for Computer Vision." +default_prompt: "Use this skill to help with synthetic data generation in Computer Vision." diff --git a/skills/system-prompt-architecture/SKILL.md b/skills/system-prompt-architecture/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..bf0e0b6754d2f4db1faf5672391247e01266b4ce --- /dev/null +++ b/skills/system-prompt-architecture/SKILL.md @@ -0,0 +1,29 @@ +--- +name: system-prompt-architecture +description: "Guidance for system prompt architecture in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving system prompt architecture, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# System Prompt Architecture + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for system prompt architecture. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on system prompt architecture. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/system-prompt-architecture/agents/openai.yaml b/skills/system-prompt-architecture/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3bb1c2f6d7c6f44c52a142b6f347fa8256ee4068 --- /dev/null +++ b/skills/system-prompt-architecture/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "System Prompt Architecture" +short_description: "Work on system prompt architecture for LLM Engineering." +default_prompt: "Use this skill to help with system prompt architecture in LLM Engineering." diff --git a/skills/table-understanding/SKILL.md b/skills/table-understanding/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..665c72a765c8c8477aa454c53c41fb7a34a9ea13 --- /dev/null +++ b/skills/table-understanding/SKILL.md @@ -0,0 +1,29 @@ +--- +name: table-understanding +description: "Guidance for table understanding in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving table understanding, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Table Understanding + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for table understanding. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on table understanding. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/table-understanding/agents/openai.yaml b/skills/table-understanding/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b877202adb1d710f89e43e7f2a5b7229346f025f --- /dev/null +++ b/skills/table-understanding/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Table Understanding" +short_description: "Work on table understanding for Multimodal AI." +default_prompt: "Use this skill to help with table understanding in Multimodal AI." diff --git a/skills/tabular-classification/SKILL.md b/skills/tabular-classification/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..7b6892d5e31a21f06bb6bcfb968020f9200afb01 --- /dev/null +++ b/skills/tabular-classification/SKILL.md @@ -0,0 +1,29 @@ +--- +name: tabular-classification +description: "Guidance for tabular classification in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving tabular classification, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Tabular Classification + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for tabular classification. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on tabular classification. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/tabular-classification/agents/openai.yaml b/skills/tabular-classification/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..12f4d94751d021e7d0dcf5e2763de6339292b6e0 --- /dev/null +++ b/skills/tabular-classification/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Tabular Classification" +short_description: "Work on tabular classification for Machine Learning." +default_prompt: "Use this skill to help with tabular classification in Machine Learning." diff --git a/skills/tabular-regression/SKILL.md b/skills/tabular-regression/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..21fe9360b9c6c74a663dec8233af65cad6b59eff --- /dev/null +++ b/skills/tabular-regression/SKILL.md @@ -0,0 +1,29 @@ +--- +name: tabular-regression +description: "Guidance for tabular regression in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving tabular regression, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Tabular Regression + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for tabular regression. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on tabular regression. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/tabular-regression/agents/openai.yaml b/skills/tabular-regression/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..32640591346cb5765401a2fe2e3a390fe3a03b47 --- /dev/null +++ b/skills/tabular-regression/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Tabular Regression" +short_description: "Work on tabular regression for Machine Learning." +default_prompt: "Use this skill to help with tabular regression in Machine Learning." diff --git a/skills/task-decomposition/SKILL.md b/skills/task-decomposition/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..9b974e1c4fea61b572a3d480dbbf2d9ba10b3ea9 --- /dev/null +++ b/skills/task-decomposition/SKILL.md @@ -0,0 +1,29 @@ +--- +name: task-decomposition +description: "Guidance for task decomposition in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving task decomposition, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Task Decomposition + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for task decomposition. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on task decomposition. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/task-decomposition/agents/openai.yaml b/skills/task-decomposition/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..4f9c672945993108958124ca8d5705f37e0899c7 --- /dev/null +++ b/skills/task-decomposition/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Task Decomposition" +short_description: "Work on task decomposition for Agentic AI." +default_prompt: "Use this skill to help with task decomposition in Agentic AI." diff --git a/skills/tensor-shape-debugging/SKILL.md b/skills/tensor-shape-debugging/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..e500cbcd998d9dd070593a16c32e0f53262949e7 --- /dev/null +++ b/skills/tensor-shape-debugging/SKILL.md @@ -0,0 +1,29 @@ +--- +name: tensor-shape-debugging +description: "Guidance for tensor shape debugging in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving tensor shape debugging, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Tensor Shape Debugging + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for tensor shape debugging. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on tensor shape debugging. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/tensor-shape-debugging/agents/openai.yaml b/skills/tensor-shape-debugging/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..a9b5470b3de26bcf54f14403af9e4319412873a5 --- /dev/null +++ b/skills/tensor-shape-debugging/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Tensor Shape Debugging" +short_description: "Work on tensor shape debugging for Deep Learning." +default_prompt: "Use this skill to help with tensor shape debugging in Deep Learning." diff --git a/skills/terraform-modules/SKILL.md b/skills/terraform-modules/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..b5f3e155e8441e413bd0d4d2e646b617bc05eb41 --- /dev/null +++ b/skills/terraform-modules/SKILL.md @@ -0,0 +1,29 @@ +--- +name: terraform-modules +description: "Guidance for Terraform modules in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving Terraform modules, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# Terraform Modules + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for Terraform modules. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on Terraform modules. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/terraform-modules/agents/openai.yaml b/skills/terraform-modules/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9e1bced7e4be47a434f26f521e4f24b848e1d41e --- /dev/null +++ b/skills/terraform-modules/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Terraform Modules" +short_description: "Work on Terraform modules for Cloud And DevOps." +default_prompt: "Use this skill to help with Terraform modules in Cloud And DevOps." diff --git a/skills/text-classification/SKILL.md b/skills/text-classification/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..7c65e143e6500c8e9031888052ae709cc61ea632 --- /dev/null +++ b/skills/text-classification/SKILL.md @@ -0,0 +1,29 @@ +--- +name: text-classification +description: "Guidance for text classification in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving text classification, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Text Classification + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for text classification. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on text classification. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/text-classification/agents/openai.yaml b/skills/text-classification/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9d7571ca37274a17ee47f41b7d90ab55785630af --- /dev/null +++ b/skills/text-classification/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Text Classification" +short_description: "Work on text classification for Natural Language Processing." +default_prompt: "Use this skill to help with text classification in Natural Language Processing." diff --git a/skills/text-generation/SKILL.md b/skills/text-generation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..89074e96a66b99b586d599dfe82ac07e7b7753ee --- /dev/null +++ b/skills/text-generation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: text-generation +description: "Guidance for text generation in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving text generation, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Text Generation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for text generation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on text generation. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/text-generation/agents/openai.yaml b/skills/text-generation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9649c7dd93536a7d7dc2dcf2d2f9e8253fa275e7 --- /dev/null +++ b/skills/text-generation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Text Generation" +short_description: "Work on text generation for Natural Language Processing." +default_prompt: "Use this skill to help with text generation in Natural Language Processing." diff --git a/skills/text-image-alignment/SKILL.md b/skills/text-image-alignment/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..43bcaa7587ff6e5e90c7a299c64d273a7f6beada --- /dev/null +++ b/skills/text-image-alignment/SKILL.md @@ -0,0 +1,29 @@ +--- +name: text-image-alignment +description: "Guidance for text image alignment in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving text image alignment, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Text Image Alignment + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for text image alignment. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on text image alignment. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/text-image-alignment/agents/openai.yaml b/skills/text-image-alignment/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..1d2f614ae16e1f56e8ba8b247d0fbe0365b1f7f3 --- /dev/null +++ b/skills/text-image-alignment/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Text Image Alignment" +short_description: "Work on text image alignment for Multimodal AI." +default_prompt: "Use this skill to help with text image alignment in Multimodal AI." diff --git a/skills/text-normalization/SKILL.md b/skills/text-normalization/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..76bd94a84e0ec5f35b4f9fd8d7a6cb6b90a4ea9d --- /dev/null +++ b/skills/text-normalization/SKILL.md @@ -0,0 +1,29 @@ +--- +name: text-normalization +description: "Guidance for text normalization in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving text normalization, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Text Normalization + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for text normalization. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on text normalization. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/text-normalization/agents/openai.yaml b/skills/text-normalization/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..dd00dfec66d6ad2cfdab0c31b54b761095fb2d8c --- /dev/null +++ b/skills/text-normalization/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Text Normalization" +short_description: "Work on text normalization for Natural Language Processing." +default_prompt: "Use this skill to help with text normalization in Natural Language Processing." diff --git a/skills/text-to-speech/SKILL.md b/skills/text-to-speech/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..647f5f49d84bacfd5a0e121f6c4a59caa7341b3e --- /dev/null +++ b/skills/text-to-speech/SKILL.md @@ -0,0 +1,29 @@ +--- +name: text-to-speech +description: "Guidance for text to speech in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving text to speech, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Text To Speech + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for text to speech. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on text to speech. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/text-to-speech/agents/openai.yaml b/skills/text-to-speech/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9a7314ff6b317d806a4bb8c7ccffcd41fce12cb8 --- /dev/null +++ b/skills/text-to-speech/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Text To Speech" +short_description: "Work on text to speech for Speech And Audio." +default_prompt: "Use this skill to help with text to speech in Speech And Audio." diff --git a/skills/threat-modeling/SKILL.md b/skills/threat-modeling/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..6167ac29f9be5ff92341da0ae6d4bfd100e28ebe --- /dev/null +++ b/skills/threat-modeling/SKILL.md @@ -0,0 +1,29 @@ +--- +name: threat-modeling +description: "Guidance for threat modeling in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving threat modeling, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# Threat Modeling + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for threat modeling. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on threat modeling. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/threat-modeling/agents/openai.yaml b/skills/threat-modeling/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3f493ddcc557c003c9c50329909c5aa8a544ab32 --- /dev/null +++ b/skills/threat-modeling/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Threat Modeling" +short_description: "Work on threat modeling for Security And Privacy." +default_prompt: "Use this skill to help with threat modeling in Security And Privacy." diff --git a/skills/time-series-databases/SKILL.md b/skills/time-series-databases/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..f821bc9f161c9902a1ccfde3b614bfe156b09719 --- /dev/null +++ b/skills/time-series-databases/SKILL.md @@ -0,0 +1,29 @@ +--- +name: time-series-databases +description: "Guidance for time series databases in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving time series databases, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# Time Series Databases + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for time series databases. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on time series databases. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/time-series-databases/agents/openai.yaml b/skills/time-series-databases/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..a3905ef4c5e41e1bbd278f5cfb0f1abcfcbeef0a --- /dev/null +++ b/skills/time-series-databases/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Time Series Databases" +short_description: "Work on time series databases for Databases And Analytics." +default_prompt: "Use this skill to help with time series databases in Databases And Analytics." diff --git a/skills/time-series-forecasting/SKILL.md b/skills/time-series-forecasting/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..c736858aca2c7e2db4bb6f50faa77b74c4b0a6e1 --- /dev/null +++ b/skills/time-series-forecasting/SKILL.md @@ -0,0 +1,29 @@ +--- +name: time-series-forecasting +description: "Guidance for time series forecasting in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving time series forecasting, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Time Series Forecasting + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for time series forecasting. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on time series forecasting. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/time-series-forecasting/agents/openai.yaml b/skills/time-series-forecasting/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..0f956ae89bf1821827c8305ed28044285b40f406 --- /dev/null +++ b/skills/time-series-forecasting/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Time Series Forecasting" +short_description: "Work on time series forecasting for Machine Learning." +default_prompt: "Use this skill to help with time series forecasting in Machine Learning." diff --git a/skills/token-budget-control/SKILL.md b/skills/token-budget-control/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..5cd9f46067cb455b9ad51b1217722f677fff448d --- /dev/null +++ b/skills/token-budget-control/SKILL.md @@ -0,0 +1,29 @@ +--- +name: token-budget-control +description: "Guidance for token budget control in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving token budget control, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Token Budget Control + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for token budget control. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on token budget control. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/token-budget-control/agents/openai.yaml b/skills/token-budget-control/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..761cb0c60e3049a3639def5aaa49e81ab3a9da77 --- /dev/null +++ b/skills/token-budget-control/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Token Budget Control" +short_description: "Work on token budget control for LLM Engineering." +default_prompt: "Use this skill to help with token budget control in LLM Engineering." diff --git a/skills/tokenization-strategy/SKILL.md b/skills/tokenization-strategy/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..d7088e6af5df698a0b2dc4ce58ffaf7fe5a6b282 --- /dev/null +++ b/skills/tokenization-strategy/SKILL.md @@ -0,0 +1,29 @@ +--- +name: tokenization-strategy +description: "Guidance for tokenization strategy in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving tokenization strategy, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Tokenization Strategy + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for tokenization strategy. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on tokenization strategy. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/tokenization-strategy/agents/openai.yaml b/skills/tokenization-strategy/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..db0e9af0a448dfc42c63e16a4236a676a44ab379 --- /dev/null +++ b/skills/tokenization-strategy/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Tokenization Strategy" +short_description: "Work on tokenization strategy for Natural Language Processing." +default_prompt: "Use this skill to help with tokenization strategy in Natural Language Processing." diff --git a/skills/tool-calling-contracts/SKILL.md b/skills/tool-calling-contracts/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..03fd533de56134e52168c47e70134ddec7f8877f --- /dev/null +++ b/skills/tool-calling-contracts/SKILL.md @@ -0,0 +1,29 @@ +--- +name: tool-calling-contracts +description: "Guidance for tool calling contracts in LLM Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving tool calling contracts, llm engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Tool Calling Contracts + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for tool calling contracts. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a LLM Engineering task centered on tool calling contracts. +- Define model interface contracts before coding. +- Track prompt, context, latency, and cost as first class signals. +- Add deterministic tests for schemas, tools, and failure handling. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/tool-calling-contracts/agents/openai.yaml b/skills/tool-calling-contracts/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3472ecd3c1623ff63eaa02d184cabf26ce1ecfc9 --- /dev/null +++ b/skills/tool-calling-contracts/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Tool Calling Contracts" +short_description: "Work on tool calling contracts for LLM Engineering." +default_prompt: "Use this skill to help with tool calling contracts in LLM Engineering." diff --git a/skills/tool-sandbox-design/SKILL.md b/skills/tool-sandbox-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..69fd02ebcaea1fe16257738925c878e0764d4333 --- /dev/null +++ b/skills/tool-sandbox-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: tool-sandbox-design +description: "Guidance for tool sandbox design in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving tool sandbox design, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Tool Sandbox Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for tool sandbox design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on tool sandbox design. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/tool-sandbox-design/agents/openai.yaml b/skills/tool-sandbox-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..33514a8fdc19a6683edc474f389c51b432efab40 --- /dev/null +++ b/skills/tool-sandbox-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Tool Sandbox Design" +short_description: "Work on tool sandbox design for Agentic AI." +default_prompt: "Use this skill to help with tool sandbox design in Agentic AI." diff --git a/skills/topic-modeling/SKILL.md b/skills/topic-modeling/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..8eeced3f354020220ce4f6b8cbcc47df16ce4e6f --- /dev/null +++ b/skills/topic-modeling/SKILL.md @@ -0,0 +1,29 @@ +--- +name: topic-modeling +description: "Guidance for topic modeling in Natural Language Processing. Use when Codex needs to plan, build, review, test, debug, or document work involving topic modeling, natural language processing, AI systems, software delivery, data workflows, or model quality." +--- + +# Topic Modeling + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for topic modeling. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Natural Language Processing task centered on topic modeling. +- Inspect raw text, labels, tokenization, and language coverage. +- Preserve document boundaries and metadata where they affect meaning. +- Evaluate on realistic samples, not only aggregate metrics. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/topic-modeling/agents/openai.yaml b/skills/topic-modeling/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..78d6ab67b3a5dc7be1688b3e74a5c88b177e38a6 --- /dev/null +++ b/skills/topic-modeling/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Topic Modeling" +short_description: "Work on topic modeling for Natural Language Processing." +default_prompt: "Use this skill to help with topic modeling in Natural Language Processing." diff --git a/skills/toxicity-evaluation/SKILL.md b/skills/toxicity-evaluation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..2aa8de45e455958f296c34f97e947714eb26a3a5 --- /dev/null +++ b/skills/toxicity-evaluation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: toxicity-evaluation +description: "Guidance for toxicity evaluation in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving toxicity evaluation, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# Toxicity Evaluation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for toxicity evaluation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on toxicity evaluation. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/toxicity-evaluation/agents/openai.yaml b/skills/toxicity-evaluation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..f68fec3d03c5df6b7842aa4b9714e9cd0114d42b --- /dev/null +++ b/skills/toxicity-evaluation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Toxicity Evaluation" +short_description: "Work on toxicity evaluation for Prompting And Evaluation." +default_prompt: "Use this skill to help with toxicity evaluation in Prompting And Evaluation." diff --git a/skills/tracking-systems/SKILL.md b/skills/tracking-systems/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..f5c88d5f9042507dd87a669dcf972a6711390413 --- /dev/null +++ b/skills/tracking-systems/SKILL.md @@ -0,0 +1,29 @@ +--- +name: tracking-systems +description: "Guidance for tracking systems in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving tracking systems, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Tracking Systems + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for tracking systems. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on tracking systems. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/tracking-systems/agents/openai.yaml b/skills/tracking-systems/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..281e93ebc2f9ce004ed1a49dab38168279465cb6 --- /dev/null +++ b/skills/tracking-systems/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Tracking Systems" +short_description: "Work on tracking systems for Computer Vision." +default_prompt: "Use this skill to help with tracking systems in Computer Vision." diff --git a/skills/training-loop-instrumentation/SKILL.md b/skills/training-loop-instrumentation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..149dc6d6d0c3fb4d40209d418e27383366e573f0 --- /dev/null +++ b/skills/training-loop-instrumentation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: training-loop-instrumentation +description: "Guidance for training loop instrumentation in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving training loop instrumentation, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Training Loop Instrumentation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for training loop instrumentation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on training loop instrumentation. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/training-loop-instrumentation/agents/openai.yaml b/skills/training-loop-instrumentation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d280b609a6a21d9f4eae8262e69f67e73112dccd --- /dev/null +++ b/skills/training-loop-instrumentation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Training Loop Instrumentation" +short_description: "Work on training loop instrumentation for Deep Learning." +default_prompt: "Use this skill to help with training loop instrumentation in Deep Learning." diff --git a/skills/training-pipelines/SKILL.md b/skills/training-pipelines/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a956ebf73f7052d8de1fc97e0275b61d2d52d758 --- /dev/null +++ b/skills/training-pipelines/SKILL.md @@ -0,0 +1,29 @@ +--- +name: training-pipelines +description: "Guidance for training pipelines in MLOps. Use when Codex needs to plan, build, review, test, debug, or document work involving training pipelines, mlops, AI systems, software delivery, data workflows, or model quality." +--- + +# Training Pipelines + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for training pipelines. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a MLOps task centered on training pipelines. +- Version datasets, code, configs, and model artifacts together. +- Define deploy, monitor, rollback, and incident paths. +- Automate repeatable training and serving checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/training-pipelines/agents/openai.yaml b/skills/training-pipelines/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..05c6d384eb463889e51c6594801cac7bd67126fb --- /dev/null +++ b/skills/training-pipelines/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Training Pipelines" +short_description: "Work on training pipelines for MLOps." +default_prompt: "Use this skill to help with training pipelines in MLOps." diff --git a/skills/transaction-design/SKILL.md b/skills/transaction-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..db2aa3c8d698d59f31da048c2a9764ba303f5271 --- /dev/null +++ b/skills/transaction-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: transaction-design +description: "Guidance for transaction design in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving transaction design, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# Transaction Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for transaction design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on transaction design. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/transaction-design/agents/openai.yaml b/skills/transaction-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..541e842b508e854d80e55aa0434e301e591cf243 --- /dev/null +++ b/skills/transaction-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Transaction Design" +short_description: "Work on transaction design for Databases And Analytics." +default_prompt: "Use this skill to help with transaction design in Databases And Analytics." diff --git a/skills/transcript-cleanup/SKILL.md b/skills/transcript-cleanup/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..48c022433daf16629847e407349eca1789155803 --- /dev/null +++ b/skills/transcript-cleanup/SKILL.md @@ -0,0 +1,29 @@ +--- +name: transcript-cleanup +description: "Guidance for transcript cleanup in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving transcript cleanup, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Transcript Cleanup + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for transcript cleanup. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on transcript cleanup. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/transcript-cleanup/agents/openai.yaml b/skills/transcript-cleanup/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..f87399d41f52f6c7be54100efef1c621c628ba33 --- /dev/null +++ b/skills/transcript-cleanup/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Transcript Cleanup" +short_description: "Work on transcript cleanup for Speech And Audio." +default_prompt: "Use this skill to help with transcript cleanup in Speech And Audio." diff --git a/skills/transformer-architecture/SKILL.md b/skills/transformer-architecture/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..1f087a1651b10a8fdd944062fa544eb5fcca3e6b --- /dev/null +++ b/skills/transformer-architecture/SKILL.md @@ -0,0 +1,29 @@ +--- +name: transformer-architecture +description: "Guidance for transformer architecture in Deep Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving transformer architecture, deep learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Transformer Architecture + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for transformer architecture. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Deep Learning task centered on transformer architecture. +- Verify tensor shapes and data ranges early. +- Track checkpoints, seeds, metrics, and hardware assumptions. +- Prefer proven training recipes before novel architecture changes. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/transformer-architecture/agents/openai.yaml b/skills/transformer-architecture/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..a4a4265b9f7a4a5db9c31fd20391a9a5f61ce4de --- /dev/null +++ b/skills/transformer-architecture/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Transformer Architecture" +short_description: "Work on transformer architecture for Deep Learning." +default_prompt: "Use this skill to help with transformer architecture in Deep Learning." diff --git a/skills/ui-automation-perception/SKILL.md b/skills/ui-automation-perception/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..3ffd5ab4dd9148410148acfe8a7ff3dc2e23f20c --- /dev/null +++ b/skills/ui-automation-perception/SKILL.md @@ -0,0 +1,29 @@ +--- +name: ui-automation-perception +description: "Guidance for UI automation perception in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving UI automation perception, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# UI Automation Perception + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for UI automation perception. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on UI automation perception. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/ui-automation-perception/agents/openai.yaml b/skills/ui-automation-perception/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..71931a7cc0e83fd42d0c0cac210fef6d33e7959f --- /dev/null +++ b/skills/ui-automation-perception/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "UI Automation Perception" +short_description: "Work on UI automation perception for Multimodal AI." +default_prompt: "Use this skill to help with UI automation perception in Multimodal AI." diff --git a/skills/uplift-modeling/SKILL.md b/skills/uplift-modeling/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a1415923033ea317d4f536c4b0a658d5afb0adf9 --- /dev/null +++ b/skills/uplift-modeling/SKILL.md @@ -0,0 +1,29 @@ +--- +name: uplift-modeling +description: "Guidance for uplift modeling in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving uplift modeling, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Uplift Modeling + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for uplift modeling. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on uplift modeling. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/uplift-modeling/agents/openai.yaml b/skills/uplift-modeling/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e3922453c18ea4604442d3366306fd6074e263dd --- /dev/null +++ b/skills/uplift-modeling/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Uplift Modeling" +short_description: "Work on uplift modeling for Machine Learning." +default_prompt: "Use this skill to help with uplift modeling in Machine Learning." diff --git a/skills/usage-metering-ux/SKILL.md b/skills/usage-metering-ux/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..4daa0768ca5e63513e3e2322259d40bf281df818 --- /dev/null +++ b/skills/usage-metering-ux/SKILL.md @@ -0,0 +1,29 @@ +--- +name: usage-metering-ux +description: "Guidance for usage metering UX in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving usage metering UX, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# Usage Metering UX + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for usage metering UX. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on usage metering UX. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/usage-metering-ux/agents/openai.yaml b/skills/usage-metering-ux/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..29b6cf0aaa0dc60562e69d76e9ecf2be90da5922 --- /dev/null +++ b/skills/usage-metering-ux/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Usage Metering UX" +short_description: "Work on usage metering UX for AI Product And UX." +default_prompt: "Use this skill to help with usage metering UX in AI Product And UX." diff --git a/skills/user-feedback-labeling/SKILL.md b/skills/user-feedback-labeling/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..87a26ab3c473c12703b8db3ec3b3b7d87c4430ad --- /dev/null +++ b/skills/user-feedback-labeling/SKILL.md @@ -0,0 +1,29 @@ +--- +name: user-feedback-labeling +description: "Guidance for user feedback labeling in Prompting And Evaluation. Use when Codex needs to plan, build, review, test, debug, or document work involving user feedback labeling, prompting and evaluation, AI systems, software delivery, data workflows, or model quality." +--- + +# User Feedback Labeling + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for user feedback labeling. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Prompting And Evaluation task centered on user feedback labeling. +- Create representative positive, negative, and adversarial examples. +- Separate prompt changes from model changes during evaluation. +- Use measurable rubrics instead of vague quality language. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/user-feedback-labeling/agents/openai.yaml b/skills/user-feedback-labeling/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3198e456728af49ca8f4c4458d3e71cbbce2b965 --- /dev/null +++ b/skills/user-feedback-labeling/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "User Feedback Labeling" +short_description: "Work on user feedback labeling for Prompting And Evaluation." +default_prompt: "Use this skill to help with user feedback labeling in Prompting And Evaluation." diff --git a/skills/user-trust-signals/SKILL.md b/skills/user-trust-signals/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..0f61c5d04b54b9b5f23969b376f796fe9ebf9265 --- /dev/null +++ b/skills/user-trust-signals/SKILL.md @@ -0,0 +1,29 @@ +--- +name: user-trust-signals +description: "Guidance for user trust signals in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving user trust signals, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# User Trust Signals + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for user trust signals. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on user trust signals. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/user-trust-signals/agents/openai.yaml b/skills/user-trust-signals/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e83be434fdc5776e41826ecd0356522743078d44 --- /dev/null +++ b/skills/user-trust-signals/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "User Trust Signals" +short_description: "Work on user trust signals for AI Product And UX." +default_prompt: "Use this skill to help with user trust signals in AI Product And UX." diff --git a/skills/vector-database-design/SKILL.md b/skills/vector-database-design/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..35f0bdd24927426992dcd2fb102c9fd358c9967b --- /dev/null +++ b/skills/vector-database-design/SKILL.md @@ -0,0 +1,29 @@ +--- +name: vector-database-design +description: "Guidance for vector database design in Databases And Analytics. Use when Codex needs to plan, build, review, test, debug, or document work involving vector database design, databases and analytics, AI systems, software delivery, data workflows, or model quality." +--- + +# Vector Database Design + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for vector database design. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Databases And Analytics task centered on vector database design. +- Start from query patterns and data ownership. +- Validate indexes, constraints, migrations, and rollback plans. +- Define metrics in one governed layer when possible. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/vector-database-design/agents/openai.yaml b/skills/vector-database-design/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..681f45f2fb06711609145bde10e323200d283935 --- /dev/null +++ b/skills/vector-database-design/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Vector Database Design" +short_description: "Work on vector database design for Databases And Analytics." +default_prompt: "Use this skill to help with vector database design in Databases And Analytics." diff --git a/skills/video-classification/SKILL.md b/skills/video-classification/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..ff4cf2f7bdd28b592c57ff87a9bb1a71b272779c --- /dev/null +++ b/skills/video-classification/SKILL.md @@ -0,0 +1,29 @@ +--- +name: video-classification +description: "Guidance for video classification in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving video classification, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Video Classification + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for video classification. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on video classification. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/video-classification/agents/openai.yaml b/skills/video-classification/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d54893ae82cb970cbcdbd0544439d08cf8ec5f7c --- /dev/null +++ b/skills/video-classification/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Video Classification" +short_description: "Work on video classification for Computer Vision." +default_prompt: "Use this skill to help with video classification in Computer Vision." diff --git a/skills/video-question-answering/SKILL.md b/skills/video-question-answering/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..afb98ae4480e88d580d49262357e2108d0c5e775 --- /dev/null +++ b/skills/video-question-answering/SKILL.md @@ -0,0 +1,29 @@ +--- +name: video-question-answering +description: "Guidance for video question answering in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving video question answering, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Video Question Answering + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for video question answering. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on video question answering. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/video-question-answering/agents/openai.yaml b/skills/video-question-answering/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..80193d7e06a08fa0ce8c050f78fb97f831976389 --- /dev/null +++ b/skills/video-question-answering/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Video Question Answering" +short_description: "Work on video question answering for Multimodal AI." +default_prompt: "Use this skill to help with video question answering in Multimodal AI." diff --git a/skills/vision-dataset-labeling/SKILL.md b/skills/vision-dataset-labeling/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..a3797ad2db670a7f1538179b8d00f2fcae25543d --- /dev/null +++ b/skills/vision-dataset-labeling/SKILL.md @@ -0,0 +1,29 @@ +--- +name: vision-dataset-labeling +description: "Guidance for vision dataset labeling in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving vision dataset labeling, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Vision Dataset Labeling + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for vision dataset labeling. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on vision dataset labeling. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/vision-dataset-labeling/agents/openai.yaml b/skills/vision-dataset-labeling/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..edd44e56687763ed39be3faae083dd13bd257647 --- /dev/null +++ b/skills/vision-dataset-labeling/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Vision Dataset Labeling" +short_description: "Work on vision dataset labeling for Computer Vision." +default_prompt: "Use this skill to help with vision dataset labeling in Computer Vision." diff --git a/skills/vision-language-models/SKILL.md b/skills/vision-language-models/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..3ee6db152620cac927b5d4424b9c0d1643e7c40f --- /dev/null +++ b/skills/vision-language-models/SKILL.md @@ -0,0 +1,29 @@ +--- +name: vision-language-models +description: "Guidance for vision language models in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving vision language models, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Vision Language Models + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for vision language models. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on vision language models. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/vision-language-models/agents/openai.yaml b/skills/vision-language-models/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..44741b9a6a61d4c466911e5c94757d46a2a3b8af --- /dev/null +++ b/skills/vision-language-models/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Vision Language Models" +short_description: "Work on vision language models for Multimodal AI." +default_prompt: "Use this skill to help with vision language models in Multimodal AI." diff --git a/skills/vision-model-evaluation/SKILL.md b/skills/vision-model-evaluation/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..bfa947575f27969d21fe5e06f9deaf3a47bd7652 --- /dev/null +++ b/skills/vision-model-evaluation/SKILL.md @@ -0,0 +1,29 @@ +--- +name: vision-model-evaluation +description: "Guidance for vision model evaluation in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving vision model evaluation, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Vision Model Evaluation + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for vision model evaluation. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on vision model evaluation. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/vision-model-evaluation/agents/openai.yaml b/skills/vision-model-evaluation/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..608291e8936363ddec8ed8581ec2b0a981c907f1 --- /dev/null +++ b/skills/vision-model-evaluation/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Vision Model Evaluation" +short_description: "Work on vision model evaluation for Computer Vision." +default_prompt: "Use this skill to help with vision model evaluation in Computer Vision." diff --git a/skills/visual-anomaly-detection/SKILL.md b/skills/visual-anomaly-detection/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..2785ecd3558bc46fddc5135d2739baea59e48cbb --- /dev/null +++ b/skills/visual-anomaly-detection/SKILL.md @@ -0,0 +1,29 @@ +--- +name: visual-anomaly-detection +description: "Guidance for visual anomaly detection in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving visual anomaly detection, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Visual Anomaly Detection + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for visual anomaly detection. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on visual anomaly detection. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/visual-anomaly-detection/agents/openai.yaml b/skills/visual-anomaly-detection/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..c075bf1cff65ec6fe2a70d89891acf0d72bf5bcb --- /dev/null +++ b/skills/visual-anomaly-detection/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Visual Anomaly Detection" +short_description: "Work on visual anomaly detection for Computer Vision." +default_prompt: "Use this skill to help with visual anomaly detection in Computer Vision." diff --git a/skills/visual-reasoning-tests/SKILL.md b/skills/visual-reasoning-tests/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..bc43eb677ee761e4f35098e7bbf8564b6f6c9840 --- /dev/null +++ b/skills/visual-reasoning-tests/SKILL.md @@ -0,0 +1,29 @@ +--- +name: visual-reasoning-tests +description: "Guidance for visual reasoning tests in Multimodal AI. Use when Codex needs to plan, build, review, test, debug, or document work involving visual reasoning tests, multimodal ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Visual Reasoning Tests + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for visual reasoning tests. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Multimodal AI task centered on visual reasoning tests. +- Keep each modality's preprocessing and provenance visible. +- Validate cross modal alignment before model tuning. +- Use task specific examples for safety and grounding checks. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/visual-reasoning-tests/agents/openai.yaml b/skills/visual-reasoning-tests/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..92cc35b562ce53ac7801848009cc6f99b495fabe --- /dev/null +++ b/skills/visual-reasoning-tests/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Visual Reasoning Tests" +short_description: "Work on visual reasoning tests for Multimodal AI." +default_prompt: "Use this skill to help with visual reasoning tests in Multimodal AI." diff --git a/skills/visual-search/SKILL.md b/skills/visual-search/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..86039f8a803fbb490680754acc705d5140842de5 --- /dev/null +++ b/skills/visual-search/SKILL.md @@ -0,0 +1,29 @@ +--- +name: visual-search +description: "Guidance for visual search in Computer Vision. Use when Codex needs to plan, build, review, test, debug, or document work involving visual search, computer vision, AI systems, software delivery, data workflows, or model quality." +--- + +# Visual Search + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for visual search. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Computer Vision task centered on visual search. +- Inspect images visually before trusting labels. +- Separate augmentation, preprocessing, and model inference concerns. +- Measure performance across lighting, scale, occlusion, and device sources. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/visual-search/agents/openai.yaml b/skills/visual-search/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e715bff70c1f4ae6e118e4233e7f1e65b92a384d --- /dev/null +++ b/skills/visual-search/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Visual Search" +short_description: "Work on visual search for Computer Vision." +default_prompt: "Use this skill to help with visual search in Computer Vision." diff --git a/skills/voice-activity-detection/SKILL.md b/skills/voice-activity-detection/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..7e2ad8ad39baf1bd67b3860420edc016a25c75d5 --- /dev/null +++ b/skills/voice-activity-detection/SKILL.md @@ -0,0 +1,29 @@ +--- +name: voice-activity-detection +description: "Guidance for voice activity detection in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving voice activity detection, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Voice Activity Detection + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for voice activity detection. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on voice activity detection. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/voice-activity-detection/agents/openai.yaml b/skills/voice-activity-detection/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..a14d4f2e6dda0860bef874d4125ffdeb9ad854a4 --- /dev/null +++ b/skills/voice-activity-detection/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Voice Activity Detection" +short_description: "Work on voice activity detection for Speech And Audio." +default_prompt: "Use this skill to help with voice activity detection in Speech And Audio." diff --git a/skills/voice-bot-integration/SKILL.md b/skills/voice-bot-integration/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..9e2bca981ca140817c722a16aea2847fcac2cf78 --- /dev/null +++ b/skills/voice-bot-integration/SKILL.md @@ -0,0 +1,29 @@ +--- +name: voice-bot-integration +description: "Guidance for voice bot integration in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving voice bot integration, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Voice Bot Integration + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for voice bot integration. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on voice bot integration. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/voice-bot-integration/agents/openai.yaml b/skills/voice-bot-integration/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7b4cd73a526f89c75f7abe86ba08f32e6f1c842b --- /dev/null +++ b/skills/voice-bot-integration/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Voice Bot Integration" +short_description: "Work on voice bot integration for Speech And Audio." +default_prompt: "Use this skill to help with voice bot integration in Speech And Audio." diff --git a/skills/voice-cloning-safeguards/SKILL.md b/skills/voice-cloning-safeguards/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..4c2dc68d31c37ea48bcff2244115e2ca49209623 --- /dev/null +++ b/skills/voice-cloning-safeguards/SKILL.md @@ -0,0 +1,29 @@ +--- +name: voice-cloning-safeguards +description: "Guidance for voice cloning safeguards in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving voice cloning safeguards, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Voice Cloning Safeguards + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for voice cloning safeguards. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on voice cloning safeguards. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/voice-cloning-safeguards/agents/openai.yaml b/skills/voice-cloning-safeguards/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..18f9da57a51edbddcece986432bcaf5316e55dda --- /dev/null +++ b/skills/voice-cloning-safeguards/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Voice Cloning Safeguards" +short_description: "Work on voice cloning safeguards for Speech And Audio." +default_prompt: "Use this skill to help with voice cloning safeguards in Speech And Audio." diff --git a/skills/vue-application-architecture/SKILL.md b/skills/vue-application-architecture/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..f291c176bccc99e5167291b7e3db97e34573b68d --- /dev/null +++ b/skills/vue-application-architecture/SKILL.md @@ -0,0 +1,29 @@ +--- +name: vue-application-architecture +description: "Guidance for Vue application architecture in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving Vue application architecture, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Vue Application Architecture + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for Vue application architecture. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on Vue application architecture. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/vue-application-architecture/agents/openai.yaml b/skills/vue-application-architecture/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..4fe0fd85c53ce746bcfa970382a23bea5fad2c5e --- /dev/null +++ b/skills/vue-application-architecture/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Vue Application Architecture" +short_description: "Work on Vue application architecture for Web Engineering." +default_prompt: "Use this skill to help with Vue application architecture in Web Engineering." diff --git a/skills/wake-word-detection/SKILL.md b/skills/wake-word-detection/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..24e61c25692639cf994437e3fb722329a3d3cd19 --- /dev/null +++ b/skills/wake-word-detection/SKILL.md @@ -0,0 +1,29 @@ +--- +name: wake-word-detection +description: "Guidance for wake word detection in Speech And Audio. Use when Codex needs to plan, build, review, test, debug, or document work involving wake word detection, speech and audio, AI systems, software delivery, data workflows, or model quality." +--- + +# Wake Word Detection + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for wake word detection. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Speech And Audio task centered on wake word detection. +- Confirm sample rate, channels, codec, and segmentation assumptions. +- Evaluate latency and word level quality on real audio. +- Handle noisy, accented, and interrupted speech explicitly. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/wake-word-detection/agents/openai.yaml b/skills/wake-word-detection/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e24c6c6f5fa5071bb8e4764328d9d5686b78e324 --- /dev/null +++ b/skills/wake-word-detection/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Wake Word Detection" +short_description: "Work on wake word detection for Speech And Audio." +default_prompt: "Use this skill to help with wake word detection in Speech And Audio." diff --git a/skills/warehouse-modeling/SKILL.md b/skills/warehouse-modeling/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..cf506c3f2a2273135f0cee56c4e73e89922a409f --- /dev/null +++ b/skills/warehouse-modeling/SKILL.md @@ -0,0 +1,29 @@ +--- +name: warehouse-modeling +description: "Guidance for warehouse modeling in Data Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving warehouse modeling, data engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Warehouse Modeling + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for warehouse modeling. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Data Engineering task centered on warehouse modeling. +- Design idempotent jobs with clear ownership of schemas. +- Add quality checks at ingestion and publish boundaries. +- Plan backfills, late data, and observability before production. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/warehouse-modeling/agents/openai.yaml b/skills/warehouse-modeling/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..46aa91e77a5bb0faffed681c0f5f14bee8a41ad6 --- /dev/null +++ b/skills/warehouse-modeling/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Warehouse Modeling" +short_description: "Work on warehouse modeling for Data Engineering." +default_prompt: "Use this skill to help with warehouse modeling in Data Engineering." diff --git a/skills/warehouse-robotics/SKILL.md b/skills/warehouse-robotics/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..d1458c851e12c8124d4c3aa13f5f763878c39879 --- /dev/null +++ b/skills/warehouse-robotics/SKILL.md @@ -0,0 +1,29 @@ +--- +name: warehouse-robotics +description: "Guidance for warehouse robotics in Robotics And IoT. Use when Codex needs to plan, build, review, test, debug, or document work involving warehouse robotics, robotics and iot, AI systems, software delivery, data workflows, or model quality." +--- + +# Warehouse Robotics + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for warehouse robotics. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Robotics And IoT task centered on warehouse robotics. +- Account for hardware constraints, timing, and safety states. +- Test simulation and real device behavior separately. +- Design telemetry that can diagnose field failures. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/warehouse-robotics/agents/openai.yaml b/skills/warehouse-robotics/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..48762acc99e25a4a600804c53d718c4fe4a5dc0e --- /dev/null +++ b/skills/warehouse-robotics/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Warehouse Robotics" +short_description: "Work on warehouse robotics for Robotics And IoT." +default_prompt: "Use this skill to help with warehouse robotics in Robotics And IoT." diff --git a/skills/weak-supervision/SKILL.md b/skills/weak-supervision/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..71b79f5d2086d648935d9487c7ff4d3f284ca31c --- /dev/null +++ b/skills/weak-supervision/SKILL.md @@ -0,0 +1,29 @@ +--- +name: weak-supervision +description: "Guidance for weak supervision in Machine Learning. Use when Codex needs to plan, build, review, test, debug, or document work involving weak supervision, machine learning, AI systems, software delivery, data workflows, or model quality." +--- + +# Weak Supervision + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for weak supervision. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Machine Learning task centered on weak supervision. +- Start with a simple baseline and leakage checks. +- Keep train, validation, and test boundaries explicit. +- Report metrics that match the product decision. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/weak-supervision/agents/openai.yaml b/skills/weak-supervision/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e448673e52d165d13a4647280a358c45a2f65caa --- /dev/null +++ b/skills/weak-supervision/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Weak Supervision" +short_description: "Work on weak supervision for Machine Learning." +default_prompt: "Use this skill to help with weak supervision in Machine Learning." diff --git a/skills/web-accessibility/SKILL.md b/skills/web-accessibility/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..b4d789a1b91bc964e133256cf8c1041b3b49f86b --- /dev/null +++ b/skills/web-accessibility/SKILL.md @@ -0,0 +1,29 @@ +--- +name: web-accessibility +description: "Guidance for web accessibility in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving web accessibility, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Web Accessibility + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for web accessibility. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on web accessibility. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/web-accessibility/agents/openai.yaml b/skills/web-accessibility/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..71fbfc40569fd13517cefad50034c1b6f7832209 --- /dev/null +++ b/skills/web-accessibility/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Web Accessibility" +short_description: "Work on web accessibility for Web Engineering." +default_prompt: "Use this skill to help with web accessibility in Web Engineering." diff --git a/skills/web-performance/SKILL.md b/skills/web-performance/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..62c61a58c7427541f618fca0e78795567b4600b5 --- /dev/null +++ b/skills/web-performance/SKILL.md @@ -0,0 +1,29 @@ +--- +name: web-performance +description: "Guidance for web performance in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving web performance, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Web Performance + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for web performance. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on web performance. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/web-performance/agents/openai.yaml b/skills/web-performance/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..328f014c53703daf258ce884e97d774fe3162737 --- /dev/null +++ b/skills/web-performance/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Web Performance" +short_description: "Work on web performance for Web Engineering." +default_prompt: "Use this skill to help with web performance in Web Engineering." diff --git a/skills/web-security-headers/SKILL.md b/skills/web-security-headers/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..5d20be4fea2705b42fe6b073bee33e1fb52c500c --- /dev/null +++ b/skills/web-security-headers/SKILL.md @@ -0,0 +1,29 @@ +--- +name: web-security-headers +description: "Guidance for web security headers in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving web security headers, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Web Security Headers + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for web security headers. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on web security headers. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/web-security-headers/agents/openai.yaml b/skills/web-security-headers/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..f8252688b753578f4435a3f6b2c112c8a8bdc264 --- /dev/null +++ b/skills/web-security-headers/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Web Security Headers" +short_description: "Work on web security headers for Web Engineering." +default_prompt: "Use this skill to help with web security headers in Web Engineering." diff --git a/skills/websocket-features/SKILL.md b/skills/websocket-features/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..8db08ee9bb8ea5bb0d91a32fb1d968680931a0f5 --- /dev/null +++ b/skills/websocket-features/SKILL.md @@ -0,0 +1,29 @@ +--- +name: websocket-features +description: "Guidance for websocket features in Web Engineering. Use when Codex needs to plan, build, review, test, debug, or document work involving websocket features, web engineering, AI systems, software delivery, data workflows, or model quality." +--- + +# Websocket Features + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for websocket features. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Web Engineering task centered on websocket features. +- Follow the existing framework, routing, and component patterns. +- Make loading, empty, error, and mobile states explicit. +- Verify accessibility and performance before handoff. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/websocket-features/agents/openai.yaml b/skills/websocket-features/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..161c80892257fb433f3d7e922f8279a58ef2681b --- /dev/null +++ b/skills/websocket-features/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Websocket Features" +short_description: "Work on websocket features for Web Engineering." +default_prompt: "Use this skill to help with websocket features in Web Engineering." diff --git a/skills/workflow-automation-ux/SKILL.md b/skills/workflow-automation-ux/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..e84e6e846f82197344c7e77b292453c6a866abab --- /dev/null +++ b/skills/workflow-automation-ux/SKILL.md @@ -0,0 +1,29 @@ +--- +name: workflow-automation-ux +description: "Guidance for workflow automation UX in AI Product And UX. Use when Codex needs to plan, build, review, test, debug, or document work involving workflow automation UX, ai product and ux, AI systems, software delivery, data workflows, or model quality." +--- + +# Workflow Automation UX + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for workflow automation UX. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a AI Product And UX task centered on workflow automation UX. +- Start from user job, risk, and feedback loop. +- Expose uncertainty and recovery paths without clutter. +- Measure usefulness, trust, and operational burden. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/workflow-automation-ux/agents/openai.yaml b/skills/workflow-automation-ux/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..5844413052bfb8e55cb64553d41a499272fb34fe --- /dev/null +++ b/skills/workflow-automation-ux/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Workflow Automation UX" +short_description: "Work on workflow automation UX for AI Product And UX." +default_prompt: "Use this skill to help with workflow automation UX in AI Product And UX." diff --git a/skills/workflow-graph-agents/SKILL.md b/skills/workflow-graph-agents/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..85f77275dc6c143c18f68d4b618f234c19f81c8f --- /dev/null +++ b/skills/workflow-graph-agents/SKILL.md @@ -0,0 +1,29 @@ +--- +name: workflow-graph-agents +description: "Guidance for workflow graph agents in Agentic AI. Use when Codex needs to plan, build, review, test, debug, or document work involving workflow graph agents, agentic ai, AI systems, software delivery, data workflows, or model quality." +--- + +# Workflow Graph Agents + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for workflow graph agents. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Agentic AI task centered on workflow graph agents. +- Model the workflow state explicitly. +- Gate risky actions behind user approval or dry runs. +- Log each tool call, observation, and state transition for review. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/workflow-graph-agents/agents/openai.yaml b/skills/workflow-graph-agents/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..59113cc4286829dd28cf4e5fd0cce25f8193a405 --- /dev/null +++ b/skills/workflow-graph-agents/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Workflow Graph Agents" +short_description: "Work on workflow graph agents for Agentic AI." +default_prompt: "Use this skill to help with workflow graph agents in Agentic AI." diff --git a/skills/xss-prevention/SKILL.md b/skills/xss-prevention/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..4b4ca8e53b97bd473648fb43376fe406a786df91 --- /dev/null +++ b/skills/xss-prevention/SKILL.md @@ -0,0 +1,29 @@ +--- +name: xss-prevention +description: "Guidance for XSS prevention in Security And Privacy. Use when Codex needs to plan, build, review, test, debug, or document work involving XSS prevention, security and privacy, AI systems, software delivery, data workflows, or model quality." +--- + +# XSS Prevention + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for XSS prevention. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Security And Privacy task centered on XSS prevention. +- Identify assets, trust boundaries, and abuse cases first. +- Minimize sensitive data collection and retention. +- Verify controls with tests, logs, and reviewable evidence. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/xss-prevention/agents/openai.yaml b/skills/xss-prevention/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d0d1caa9322bb9c2db3b3f3dfbfa6ee2cbea7fc1 --- /dev/null +++ b/skills/xss-prevention/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "XSS Prevention" +short_description: "Work on XSS prevention for Security And Privacy." +default_prompt: "Use this skill to help with XSS prevention in Security And Privacy." diff --git a/skills/zero-downtime-deploys/SKILL.md b/skills/zero-downtime-deploys/SKILL.md new file mode 100644 index 0000000000000000000000000000000000000000..12788325bed65f851a16198fe8b5f175398b5bae --- /dev/null +++ b/skills/zero-downtime-deploys/SKILL.md @@ -0,0 +1,29 @@ +--- +name: zero-downtime-deploys +description: "Guidance for zero downtime deploys in Cloud And DevOps. Use when Codex needs to plan, build, review, test, debug, or document work involving zero downtime deploys, cloud and devops, AI systems, software delivery, data workflows, or model quality." +--- + +# Zero Downtime Deploys + +## Core Workflow + +1. Confirm the user goal, target environment, inputs, outputs, constraints, and success criteria for zero downtime deploys. +2. Inspect existing code, data, prompts, models, configs, or product flows before proposing changes. +3. Choose the smallest implementation path that fits the current system and keeps future maintenance clear. +4. Add focused validation for behavior, quality, security, privacy, cost, and operational risk where relevant. +5. Report the concrete change, verification performed, and remaining assumptions. + +## Subject Checklist + +- Treat this as a Cloud And DevOps task centered on zero downtime deploys. +- Prefer reproducible infrastructure and least privilege access. +- Document environment variables, secrets, and deployment order. +- Add monitoring, rollback, backup, and cost controls. +- Prefer existing project conventions, libraries, schemas, and deployment patterns. +- Avoid broad rewrites unless the current structure blocks a correct solution. + +## Deliverables + +- Produce implementation steps, code edits, tests, prompts, model choices, data checks, or review findings as the task requires. +- Make tradeoffs explicit: accuracy, latency, cost, safety, maintainability, and user experience. +- Leave enough context for another engineer or agent to reproduce the result. diff --git a/skills/zero-downtime-deploys/agents/openai.yaml b/skills/zero-downtime-deploys/agents/openai.yaml new file mode 100644 index 0000000000000000000000000000000000000000..8636b12929020afa7a561acba5e643a02df196a0 --- /dev/null +++ b/skills/zero-downtime-deploys/agents/openai.yaml @@ -0,0 +1,3 @@ +display_name: "Zero Downtime Deploys" +short_description: "Work on zero downtime deploys for Cloud And DevOps." +default_prompt: "Use this skill to help with zero downtime deploys in Cloud And DevOps." diff --git a/skills_index.jsonl b/skills_index.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..07869611dd1fb5e40386be97d712c0021dfd0803 --- /dev/null +++ b/skills_index.jsonl @@ -0,0 +1,500 @@ +{"name": "chat-completion-orchestration", "title": "Chat Completion Orchestration", "category": "LLM Engineering", "focus": "chat completion orchestration", "path": "skills/chat-completion-orchestration/SKILL.md"} +{"name": "retrieval-augmented-generation", "title": "Retrieval Augmented Generation", "category": "LLM Engineering", "focus": "retrieval augmented generation", "path": "skills/retrieval-augmented-generation/SKILL.md"} +{"name": "long-context-workflows", "title": "Long Context Workflows", "category": "LLM Engineering", "focus": "long context workflows", "path": "skills/long-context-workflows/SKILL.md"} +{"name": "structured-output-schemas", "title": "Structured Output Schemas", "category": "LLM Engineering", "focus": "structured output schemas", "path": "skills/structured-output-schemas/SKILL.md"} +{"name": "tool-calling-contracts", "title": "Tool Calling Contracts", "category": "LLM Engineering", "focus": "tool calling contracts", "path": "skills/tool-calling-contracts/SKILL.md"} +{"name": "function-routing", "title": "Function Routing", "category": "LLM Engineering", "focus": "function routing", "path": "skills/function-routing/SKILL.md"} +{"name": "model-fallback-strategy", "title": "Model Fallback Strategy", "category": "LLM Engineering", "focus": "model fallback strategy", "path": "skills/model-fallback-strategy/SKILL.md"} +{"name": "conversation-memory-design", "title": "Conversation Memory Design", "category": "LLM Engineering", "focus": "conversation memory design", "path": "skills/conversation-memory-design/SKILL.md"} +{"name": "token-budget-control", "title": "Token Budget Control", "category": "LLM Engineering", "focus": "token budget control", "path": "skills/token-budget-control/SKILL.md"} +{"name": "streaming-response-handling", "title": "Streaming Response Handling", "category": "LLM Engineering", "focus": "streaming response handling", "path": "skills/streaming-response-handling/SKILL.md"} +{"name": "system-prompt-architecture", "title": "System Prompt Architecture", "category": "LLM Engineering", "focus": "system prompt architecture", "path": "skills/system-prompt-architecture/SKILL.md"} +{"name": "multi-tenant-model-gateways", "title": "Multi Tenant Model Gateways", "category": "LLM Engineering", "focus": "multi tenant model gateways", "path": "skills/multi-tenant-model-gateways/SKILL.md"} +{"name": "rate-limit-resilience", "title": "Rate Limit Resilience", "category": "LLM Engineering", "focus": "rate limit resilience", "path": "skills/rate-limit-resilience/SKILL.md"} +{"name": "cost-aware-inference", "title": "Cost Aware Inference", "category": "LLM Engineering", "focus": "cost aware inference", "path": "skills/cost-aware-inference/SKILL.md"} +{"name": "safety-refusal-handling", "title": "Safety Refusal Handling", "category": "LLM Engineering", "focus": "safety refusal handling", "path": "skills/safety-refusal-handling/SKILL.md"} +{"name": "embedding-pipeline-design", "title": "Embedding Pipeline Design", "category": "LLM Engineering", "focus": "embedding pipeline design", "path": "skills/embedding-pipeline-design/SKILL.md"} +{"name": "semantic-cache-design", "title": "Semantic Cache Design", "category": "LLM Engineering", "focus": "semantic cache design", "path": "skills/semantic-cache-design/SKILL.md"} +{"name": "context-compression", "title": "Context Compression", "category": "LLM Engineering", "focus": "context compression", "path": "skills/context-compression/SKILL.md"} +{"name": "llm-observability", "title": "LLM Observability", "category": "LLM Engineering", "focus": "LLM observability", "path": "skills/llm-observability/SKILL.md"} +{"name": "prompt-injection-defense", "title": "Prompt Injection Defense", "category": "LLM Engineering", "focus": "prompt injection defense", "path": "skills/prompt-injection-defense/SKILL.md"} +{"name": "fine-tuning-data-preparation", "title": "Fine Tuning Data Preparation", "category": "LLM Engineering", "focus": "fine tuning data preparation", "path": "skills/fine-tuning-data-preparation/SKILL.md"} +{"name": "instruction-dataset-curation", "title": "Instruction Dataset Curation", "category": "LLM Engineering", "focus": "instruction dataset curation", "path": "skills/instruction-dataset-curation/SKILL.md"} +{"name": "model-selection-benchmarking", "title": "Model Selection Benchmarking", "category": "LLM Engineering", "focus": "model selection benchmarking", "path": "skills/model-selection-benchmarking/SKILL.md"} +{"name": "api-latency-optimization", "title": "API Latency Optimization", "category": "LLM Engineering", "focus": "API latency optimization", "path": "skills/api-latency-optimization/SKILL.md"} +{"name": "response-quality-debugging", "title": "Response Quality Debugging", "category": "LLM Engineering", "focus": "response quality debugging", "path": "skills/response-quality-debugging/SKILL.md"} +{"name": "planner-executor-agents", "title": "Planner Executor Agents", "category": "Agentic AI", "focus": "planner executor agents", "path": "skills/planner-executor-agents/SKILL.md"} +{"name": "react-style-reasoning-loops", "title": "React Style Reasoning Loops", "category": "Agentic AI", "focus": "react style reasoning loops", "path": "skills/react-style-reasoning-loops/SKILL.md"} +{"name": "browser-automation-agents", "title": "Browser Automation Agents", "category": "Agentic AI", "focus": "browser automation agents", "path": "skills/browser-automation-agents/SKILL.md"} +{"name": "coding-agent-workflows", "title": "Coding Agent Workflows", "category": "Agentic AI", "focus": "coding agent workflows", "path": "skills/coding-agent-workflows/SKILL.md"} +{"name": "research-agent-workflows", "title": "Research Agent Workflows", "category": "Agentic AI", "focus": "research agent workflows", "path": "skills/research-agent-workflows/SKILL.md"} +{"name": "multi-agent-coordination", "title": "Multi Agent Coordination", "category": "Agentic AI", "focus": "multi agent coordination", "path": "skills/multi-agent-coordination/SKILL.md"} +{"name": "task-decomposition", "title": "Task Decomposition", "category": "Agentic AI", "focus": "task decomposition", "path": "skills/task-decomposition/SKILL.md"} +{"name": "agent-memory-stores", "title": "Agent Memory Stores", "category": "Agentic AI", "focus": "agent memory stores", "path": "skills/agent-memory-stores/SKILL.md"} +{"name": "approval-gated-actions", "title": "Approval Gated Actions", "category": "Agentic AI", "focus": "approval gated actions", "path": "skills/approval-gated-actions/SKILL.md"} +{"name": "autonomous-retry-policy", "title": "Autonomous Retry Policy", "category": "Agentic AI", "focus": "autonomous retry policy", "path": "skills/autonomous-retry-policy/SKILL.md"} +{"name": "tool-sandbox-design", "title": "Tool Sandbox Design", "category": "Agentic AI", "focus": "tool sandbox design", "path": "skills/tool-sandbox-design/SKILL.md"} +{"name": "agent-evaluation-harnesses", "title": "Agent Evaluation Harnesses", "category": "Agentic AI", "focus": "agent evaluation harnesses", "path": "skills/agent-evaluation-harnesses/SKILL.md"} +{"name": "human-in-the-loop-review", "title": "Human In The Loop Review", "category": "Agentic AI", "focus": "human in the loop review", "path": "skills/human-in-the-loop-review/SKILL.md"} +{"name": "state-machine-agents", "title": "State Machine Agents", "category": "Agentic AI", "focus": "state machine agents", "path": "skills/state-machine-agents/SKILL.md"} +{"name": "goal-tracking", "title": "Goal Tracking", "category": "Agentic AI", "focus": "goal tracking", "path": "skills/goal-tracking/SKILL.md"} +{"name": "subtask-delegation", "title": "Subtask Delegation", "category": "Agentic AI", "focus": "subtask delegation", "path": "skills/subtask-delegation/SKILL.md"} +{"name": "agent-trace-analysis", "title": "Agent Trace Analysis", "category": "Agentic AI", "focus": "agent trace analysis", "path": "skills/agent-trace-analysis/SKILL.md"} +{"name": "workflow-graph-agents", "title": "Workflow Graph Agents", "category": "Agentic AI", "focus": "workflow graph agents", "path": "skills/workflow-graph-agents/SKILL.md"} +{"name": "event-driven-agents", "title": "Event Driven Agents", "category": "Agentic AI", "focus": "event driven agents", "path": "skills/event-driven-agents/SKILL.md"} +{"name": "personal-assistant-agents", "title": "Personal Assistant Agents", "category": "Agentic AI", "focus": "personal assistant agents", "path": "skills/personal-assistant-agents/SKILL.md"} +{"name": "enterprise-task-agents", "title": "Enterprise Task Agents", "category": "Agentic AI", "focus": "enterprise task agents", "path": "skills/enterprise-task-agents/SKILL.md"} +{"name": "file-editing-agents", "title": "File Editing Agents", "category": "Agentic AI", "focus": "file editing agents", "path": "skills/file-editing-agents/SKILL.md"} +{"name": "data-analysis-agents", "title": "Data Analysis Agents", "category": "Agentic AI", "focus": "data analysis agents", "path": "skills/data-analysis-agents/SKILL.md"} +{"name": "customer-support-agents", "title": "Customer Support Agents", "category": "Agentic AI", "focus": "customer support agents", "path": "skills/customer-support-agents/SKILL.md"} +{"name": "incident-response-agents", "title": "Incident Response Agents", "category": "Agentic AI", "focus": "incident response agents", "path": "skills/incident-response-agents/SKILL.md"} +{"name": "prompt-test-cases", "title": "Prompt Test Cases", "category": "Prompting And Evaluation", "focus": "prompt test cases", "path": "skills/prompt-test-cases/SKILL.md"} +{"name": "prompt-versioning", "title": "Prompt Versioning", "category": "Prompting And Evaluation", "focus": "prompt versioning", "path": "skills/prompt-versioning/SKILL.md"} +{"name": "rubric-based-grading", "title": "Rubric Based Grading", "category": "Prompting And Evaluation", "focus": "rubric based grading", "path": "skills/rubric-based-grading/SKILL.md"} +{"name": "golden-answer-datasets", "title": "Golden Answer Datasets", "category": "Prompting And Evaluation", "focus": "golden answer datasets", "path": "skills/golden-answer-datasets/SKILL.md"} +{"name": "adversarial-prompt-tests", "title": "Adversarial Prompt Tests", "category": "Prompting And Evaluation", "focus": "adversarial prompt tests", "path": "skills/adversarial-prompt-tests/SKILL.md"} +{"name": "few-shot-example-design", "title": "Few Shot Example Design", "category": "Prompting And Evaluation", "focus": "few shot example design", "path": "skills/few-shot-example-design/SKILL.md"} +{"name": "chain-of-thought-redaction", "title": "Chain Of Thought Redaction", "category": "Prompting And Evaluation", "focus": "chain of thought redaction", "path": "skills/chain-of-thought-redaction/SKILL.md"} +{"name": "prompt-migration", "title": "Prompt Migration", "category": "Prompting And Evaluation", "focus": "prompt migration", "path": "skills/prompt-migration/SKILL.md"} +{"name": "prompt-localization", "title": "Prompt Localization", "category": "Prompting And Evaluation", "focus": "prompt localization", "path": "skills/prompt-localization/SKILL.md"} +{"name": "prompt-governance", "title": "Prompt Governance", "category": "Prompting And Evaluation", "focus": "prompt governance", "path": "skills/prompt-governance/SKILL.md"} +{"name": "regression-eval-suites", "title": "Regression Eval Suites", "category": "Prompting And Evaluation", "focus": "regression eval suites", "path": "skills/regression-eval-suites/SKILL.md"} +{"name": "pairwise-model-comparison", "title": "Pairwise Model Comparison", "category": "Prompting And Evaluation", "focus": "pairwise model comparison", "path": "skills/pairwise-model-comparison/SKILL.md"} +{"name": "llm-judge-calibration", "title": "LLM Judge Calibration", "category": "Prompting And Evaluation", "focus": "LLM judge calibration", "path": "skills/llm-judge-calibration/SKILL.md"} +{"name": "bias-evaluation", "title": "Bias Evaluation", "category": "Prompting And Evaluation", "focus": "bias evaluation", "path": "skills/bias-evaluation/SKILL.md"} +{"name": "toxicity-evaluation", "title": "Toxicity Evaluation", "category": "Prompting And Evaluation", "focus": "toxicity evaluation", "path": "skills/toxicity-evaluation/SKILL.md"} +{"name": "hallucination-measurement", "title": "Hallucination Measurement", "category": "Prompting And Evaluation", "focus": "hallucination measurement", "path": "skills/hallucination-measurement/SKILL.md"} +{"name": "groundedness-scoring", "title": "Groundedness Scoring", "category": "Prompting And Evaluation", "focus": "groundedness scoring", "path": "skills/groundedness-scoring/SKILL.md"} +{"name": "answer-citation-checks", "title": "Answer Citation Checks", "category": "Prompting And Evaluation", "focus": "answer citation checks", "path": "skills/answer-citation-checks/SKILL.md"} +{"name": "instruction-hierarchy-checks", "title": "Instruction Hierarchy Checks", "category": "Prompting And Evaluation", "focus": "instruction hierarchy checks", "path": "skills/instruction-hierarchy-checks/SKILL.md"} +{"name": "role-prompt-hardening", "title": "Role Prompt Hardening", "category": "Prompting And Evaluation", "focus": "role prompt hardening", "path": "skills/role-prompt-hardening/SKILL.md"} +{"name": "prompt-cost-profiling", "title": "Prompt Cost Profiling", "category": "Prompting And Evaluation", "focus": "prompt cost profiling", "path": "skills/prompt-cost-profiling/SKILL.md"} +{"name": "prompt-latency-profiling", "title": "Prompt Latency Profiling", "category": "Prompting And Evaluation", "focus": "prompt latency profiling", "path": "skills/prompt-latency-profiling/SKILL.md"} +{"name": "offline-eval-reporting", "title": "Offline Eval Reporting", "category": "Prompting And Evaluation", "focus": "offline eval reporting", "path": "skills/offline-eval-reporting/SKILL.md"} +{"name": "online-eval-monitoring", "title": "Online Eval Monitoring", "category": "Prompting And Evaluation", "focus": "online eval monitoring", "path": "skills/online-eval-monitoring/SKILL.md"} +{"name": "user-feedback-labeling", "title": "User Feedback Labeling", "category": "Prompting And Evaluation", "focus": "user feedback labeling", "path": "skills/user-feedback-labeling/SKILL.md"} +{"name": "tabular-classification", "title": "Tabular Classification", "category": "Machine Learning", "focus": "tabular classification", "path": "skills/tabular-classification/SKILL.md"} +{"name": "tabular-regression", "title": "Tabular Regression", "category": "Machine Learning", "focus": "tabular regression", "path": "skills/tabular-regression/SKILL.md"} +{"name": "feature-engineering", "title": "Feature Engineering", "category": "Machine Learning", "focus": "feature engineering", "path": "skills/feature-engineering/SKILL.md"} +{"name": "cross-validation-design", "title": "Cross Validation Design", "category": "Machine Learning", "focus": "cross validation design", "path": "skills/cross-validation-design/SKILL.md"} +{"name": "class-imbalance-handling", "title": "Class Imbalance Handling", "category": "Machine Learning", "focus": "class imbalance handling", "path": "skills/class-imbalance-handling/SKILL.md"} +{"name": "time-series-forecasting", "title": "Time Series Forecasting", "category": "Machine Learning", "focus": "time series forecasting", "path": "skills/time-series-forecasting/SKILL.md"} +{"name": "anomaly-detection", "title": "Anomaly Detection", "category": "Machine Learning", "focus": "anomaly detection", "path": "skills/anomaly-detection/SKILL.md"} +{"name": "recommendation-systems", "title": "Recommendation Systems", "category": "Machine Learning", "focus": "recommendation systems", "path": "skills/recommendation-systems/SKILL.md"} +{"name": "ranking-models", "title": "Ranking Models", "category": "Machine Learning", "focus": "ranking models", "path": "skills/ranking-models/SKILL.md"} +{"name": "clustering-workflows", "title": "Clustering Workflows", "category": "Machine Learning", "focus": "clustering workflows", "path": "skills/clustering-workflows/SKILL.md"} +{"name": "dimensionality-reduction", "title": "Dimensionality Reduction", "category": "Machine Learning", "focus": "dimensionality reduction", "path": "skills/dimensionality-reduction/SKILL.md"} +{"name": "survival-analysis", "title": "Survival Analysis", "category": "Machine Learning", "focus": "survival analysis", "path": "skills/survival-analysis/SKILL.md"} +{"name": "causal-inference", "title": "Causal Inference", "category": "Machine Learning", "focus": "causal inference", "path": "skills/causal-inference/SKILL.md"} +{"name": "uplift-modeling", "title": "Uplift Modeling", "category": "Machine Learning", "focus": "uplift modeling", "path": "skills/uplift-modeling/SKILL.md"} +{"name": "semi-supervised-learning", "title": "Semi Supervised Learning", "category": "Machine Learning", "focus": "semi supervised learning", "path": "skills/semi-supervised-learning/SKILL.md"} +{"name": "active-learning", "title": "Active Learning", "category": "Machine Learning", "focus": "active learning", "path": "skills/active-learning/SKILL.md"} +{"name": "weak-supervision", "title": "Weak Supervision", "category": "Machine Learning", "focus": "weak supervision", "path": "skills/weak-supervision/SKILL.md"} +{"name": "model-calibration", "title": "Model Calibration", "category": "Machine Learning", "focus": "model calibration", "path": "skills/model-calibration/SKILL.md"} +{"name": "hyperparameter-optimization", "title": "Hyperparameter Optimization", "category": "Machine Learning", "focus": "hyperparameter optimization", "path": "skills/hyperparameter-optimization/SKILL.md"} +{"name": "feature-selection", "title": "Feature Selection", "category": "Machine Learning", "focus": "feature selection", "path": "skills/feature-selection/SKILL.md"} +{"name": "data-leakage-audits", "title": "Data Leakage Audits", "category": "Machine Learning", "focus": "data leakage audits", "path": "skills/data-leakage-audits/SKILL.md"} +{"name": "model-explainability", "title": "Model Explainability", "category": "Machine Learning", "focus": "model explainability", "path": "skills/model-explainability/SKILL.md"} +{"name": "ensemble-methods", "title": "Ensemble Methods", "category": "Machine Learning", "focus": "ensemble methods", "path": "skills/ensemble-methods/SKILL.md"} +{"name": "baseline-modeling", "title": "Baseline Modeling", "category": "Machine Learning", "focus": "baseline modeling", "path": "skills/baseline-modeling/SKILL.md"} +{"name": "production-scoring", "title": "Production Scoring", "category": "Machine Learning", "focus": "production scoring", "path": "skills/production-scoring/SKILL.md"} +{"name": "transformer-architecture", "title": "Transformer Architecture", "category": "Deep Learning", "focus": "transformer architecture", "path": "skills/transformer-architecture/SKILL.md"} +{"name": "attention-mechanisms", "title": "Attention Mechanisms", "category": "Deep Learning", "focus": "attention mechanisms", "path": "skills/attention-mechanisms/SKILL.md"} +{"name": "cnn-model-design", "title": "CNN Model Design", "category": "Deep Learning", "focus": "CNN model design", "path": "skills/cnn-model-design/SKILL.md"} +{"name": "rnn-sequence-models", "title": "RNN Sequence Models", "category": "Deep Learning", "focus": "RNN sequence models", "path": "skills/rnn-sequence-models/SKILL.md"} +{"name": "autoencoders", "title": "Autoencoders", "category": "Deep Learning", "focus": "autoencoders", "path": "skills/autoencoders/SKILL.md"} +{"name": "gan-training", "title": "GAN Training", "category": "Deep Learning", "focus": "GAN training", "path": "skills/gan-training/SKILL.md"} +{"name": "diffusion-model-training", "title": "Diffusion Model Training", "category": "Deep Learning", "focus": "diffusion model training", "path": "skills/diffusion-model-training/SKILL.md"} +{"name": "contrastive-learning", "title": "Contrastive Learning", "category": "Deep Learning", "focus": "contrastive learning", "path": "skills/contrastive-learning/SKILL.md"} +{"name": "self-supervised-learning", "title": "Self Supervised Learning", "category": "Deep Learning", "focus": "self supervised learning", "path": "skills/self-supervised-learning/SKILL.md"} +{"name": "metric-learning", "title": "Metric Learning", "category": "Deep Learning", "focus": "metric learning", "path": "skills/metric-learning/SKILL.md"} +{"name": "neural-architecture-search", "title": "Neural Architecture Search", "category": "Deep Learning", "focus": "neural architecture search", "path": "skills/neural-architecture-search/SKILL.md"} +{"name": "distributed-training", "title": "Distributed Training", "category": "Deep Learning", "focus": "distributed training", "path": "skills/distributed-training/SKILL.md"} +{"name": "mixed-precision-training", "title": "Mixed Precision Training", "category": "Deep Learning", "focus": "mixed precision training", "path": "skills/mixed-precision-training/SKILL.md"} +{"name": "gradient-checkpointing", "title": "Gradient Checkpointing", "category": "Deep Learning", "focus": "gradient checkpointing", "path": "skills/gradient-checkpointing/SKILL.md"} +{"name": "model-quantization", "title": "Model Quantization", "category": "Deep Learning", "focus": "model quantization", "path": "skills/model-quantization/SKILL.md"} +{"name": "model-pruning", "title": "Model Pruning", "category": "Deep Learning", "focus": "model pruning", "path": "skills/model-pruning/SKILL.md"} +{"name": "knowledge-distillation", "title": "Knowledge Distillation", "category": "Deep Learning", "focus": "knowledge distillation", "path": "skills/knowledge-distillation/SKILL.md"} +{"name": "checkpoint-management", "title": "Checkpoint Management", "category": "Deep Learning", "focus": "checkpoint management", "path": "skills/checkpoint-management/SKILL.md"} +{"name": "optimizer-selection", "title": "Optimizer Selection", "category": "Deep Learning", "focus": "optimizer selection", "path": "skills/optimizer-selection/SKILL.md"} +{"name": "learning-rate-schedules", "title": "Learning Rate Schedules", "category": "Deep Learning", "focus": "learning rate schedules", "path": "skills/learning-rate-schedules/SKILL.md"} +{"name": "loss-function-design", "title": "Loss Function Design", "category": "Deep Learning", "focus": "loss function design", "path": "skills/loss-function-design/SKILL.md"} +{"name": "regularization-strategy", "title": "Regularization Strategy", "category": "Deep Learning", "focus": "regularization strategy", "path": "skills/regularization-strategy/SKILL.md"} +{"name": "gpu-memory-debugging", "title": "GPU Memory Debugging", "category": "Deep Learning", "focus": "GPU memory debugging", "path": "skills/gpu-memory-debugging/SKILL.md"} +{"name": "tensor-shape-debugging", "title": "Tensor Shape Debugging", "category": "Deep Learning", "focus": "tensor shape debugging", "path": "skills/tensor-shape-debugging/SKILL.md"} +{"name": "training-loop-instrumentation", "title": "Training Loop Instrumentation", "category": "Deep Learning", "focus": "training loop instrumentation", "path": "skills/training-loop-instrumentation/SKILL.md"} +{"name": "text-classification", "title": "Text Classification", "category": "Natural Language Processing", "focus": "text classification", "path": "skills/text-classification/SKILL.md"} +{"name": "named-entity-recognition", "title": "Named Entity Recognition", "category": "Natural Language Processing", "focus": "named entity recognition", "path": "skills/named-entity-recognition/SKILL.md"} +{"name": "entity-linking", "title": "Entity Linking", "category": "Natural Language Processing", "focus": "entity linking", "path": "skills/entity-linking/SKILL.md"} +{"name": "relation-extraction", "title": "Relation Extraction", "category": "Natural Language Processing", "focus": "relation extraction", "path": "skills/relation-extraction/SKILL.md"} +{"name": "sentiment-analysis", "title": "Sentiment Analysis", "category": "Natural Language Processing", "focus": "sentiment analysis", "path": "skills/sentiment-analysis/SKILL.md"} +{"name": "topic-modeling", "title": "Topic Modeling", "category": "Natural Language Processing", "focus": "topic modeling", "path": "skills/topic-modeling/SKILL.md"} +{"name": "keyword-extraction", "title": "Keyword Extraction", "category": "Natural Language Processing", "focus": "keyword extraction", "path": "skills/keyword-extraction/SKILL.md"} +{"name": "summarization", "title": "Summarization", "category": "Natural Language Processing", "focus": "summarization", "path": "skills/summarization/SKILL.md"} +{"name": "machine-translation", "title": "Machine Translation", "category": "Natural Language Processing", "focus": "machine translation", "path": "skills/machine-translation/SKILL.md"} +{"name": "question-answering", "title": "Question Answering", "category": "Natural Language Processing", "focus": "question answering", "path": "skills/question-answering/SKILL.md"} +{"name": "text-generation", "title": "Text Generation", "category": "Natural Language Processing", "focus": "text generation", "path": "skills/text-generation/SKILL.md"} +{"name": "document-parsing", "title": "Document Parsing", "category": "Natural Language Processing", "focus": "document parsing", "path": "skills/document-parsing/SKILL.md"} +{"name": "semantic-search", "title": "Semantic Search", "category": "Natural Language Processing", "focus": "semantic search", "path": "skills/semantic-search/SKILL.md"} +{"name": "intent-detection", "title": "Intent Detection", "category": "Natural Language Processing", "focus": "intent detection", "path": "skills/intent-detection/SKILL.md"} +{"name": "slot-filling", "title": "Slot Filling", "category": "Natural Language Processing", "focus": "slot filling", "path": "skills/slot-filling/SKILL.md"} +{"name": "coreference-resolution", "title": "Coreference Resolution", "category": "Natural Language Processing", "focus": "coreference resolution", "path": "skills/coreference-resolution/SKILL.md"} +{"name": "text-normalization", "title": "Text Normalization", "category": "Natural Language Processing", "focus": "text normalization", "path": "skills/text-normalization/SKILL.md"} +{"name": "language-detection", "title": "Language Detection", "category": "Natural Language Processing", "focus": "language detection", "path": "skills/language-detection/SKILL.md"} +{"name": "morphological-analysis", "title": "Morphological Analysis", "category": "Natural Language Processing", "focus": "morphological analysis", "path": "skills/morphological-analysis/SKILL.md"} +{"name": "tokenization-strategy", "title": "Tokenization Strategy", "category": "Natural Language Processing", "focus": "tokenization strategy", "path": "skills/tokenization-strategy/SKILL.md"} +{"name": "ocr-text-cleanup", "title": "OCR Text Cleanup", "category": "Natural Language Processing", "focus": "OCR text cleanup", "path": "skills/ocr-text-cleanup/SKILL.md"} +{"name": "legal-document-nlp", "title": "Legal Document NLP", "category": "Natural Language Processing", "focus": "legal document NLP", "path": "skills/legal-document-nlp/SKILL.md"} +{"name": "clinical-document-nlp", "title": "Clinical Document NLP", "category": "Natural Language Processing", "focus": "clinical document NLP", "path": "skills/clinical-document-nlp/SKILL.md"} +{"name": "financial-text-nlp", "title": "Financial Text NLP", "category": "Natural Language Processing", "focus": "financial text NLP", "path": "skills/financial-text-nlp/SKILL.md"} +{"name": "multilingual-nlp", "title": "Multilingual NLP", "category": "Natural Language Processing", "focus": "multilingual NLP", "path": "skills/multilingual-nlp/SKILL.md"} +{"name": "image-classification", "title": "Image Classification", "category": "Computer Vision", "focus": "image classification", "path": "skills/image-classification/SKILL.md"} +{"name": "object-detection", "title": "Object Detection", "category": "Computer Vision", "focus": "object detection", "path": "skills/object-detection/SKILL.md"} +{"name": "semantic-segmentation", "title": "Semantic Segmentation", "category": "Computer Vision", "focus": "semantic segmentation", "path": "skills/semantic-segmentation/SKILL.md"} +{"name": "instance-segmentation", "title": "Instance Segmentation", "category": "Computer Vision", "focus": "instance segmentation", "path": "skills/instance-segmentation/SKILL.md"} +{"name": "pose-estimation", "title": "Pose Estimation", "category": "Computer Vision", "focus": "pose estimation", "path": "skills/pose-estimation/SKILL.md"} +{"name": "face-recognition", "title": "Face Recognition", "category": "Computer Vision", "focus": "face recognition", "path": "skills/face-recognition/SKILL.md"} +{"name": "visual-search", "title": "Visual Search", "category": "Computer Vision", "focus": "visual search", "path": "skills/visual-search/SKILL.md"} +{"name": "ocr-pipelines", "title": "OCR Pipelines", "category": "Computer Vision", "focus": "OCR pipelines", "path": "skills/ocr-pipelines/SKILL.md"} +{"name": "document-layout-analysis", "title": "Document Layout Analysis", "category": "Computer Vision", "focus": "document layout analysis", "path": "skills/document-layout-analysis/SKILL.md"} +{"name": "image-captioning", "title": "Image Captioning", "category": "Computer Vision", "focus": "image captioning", "path": "skills/image-captioning/SKILL.md"} +{"name": "image-quality-assessment", "title": "Image Quality Assessment", "category": "Computer Vision", "focus": "image quality assessment", "path": "skills/image-quality-assessment/SKILL.md"} +{"name": "medical-imaging", "title": "Medical Imaging", "category": "Computer Vision", "focus": "medical imaging", "path": "skills/medical-imaging/SKILL.md"} +{"name": "satellite-imagery", "title": "Satellite Imagery", "category": "Computer Vision", "focus": "satellite imagery", "path": "skills/satellite-imagery/SKILL.md"} +{"name": "video-classification", "title": "Video Classification", "category": "Computer Vision", "focus": "video classification", "path": "skills/video-classification/SKILL.md"} +{"name": "action-recognition", "title": "Action Recognition", "category": "Computer Vision", "focus": "action recognition", "path": "skills/action-recognition/SKILL.md"} +{"name": "tracking-systems", "title": "Tracking Systems", "category": "Computer Vision", "focus": "tracking systems", "path": "skills/tracking-systems/SKILL.md"} +{"name": "depth-estimation", "title": "Depth Estimation", "category": "Computer Vision", "focus": "depth estimation", "path": "skills/depth-estimation/SKILL.md"} +{"name": "stereo-vision", "title": "Stereo Vision", "category": "Computer Vision", "focus": "stereo vision", "path": "skills/stereo-vision/SKILL.md"} +{"name": "image-augmentation", "title": "Image Augmentation", "category": "Computer Vision", "focus": "image augmentation", "path": "skills/image-augmentation/SKILL.md"} +{"name": "synthetic-data-generation", "title": "Synthetic Data Generation", "category": "Computer Vision", "focus": "synthetic data generation", "path": "skills/synthetic-data-generation/SKILL.md"} +{"name": "camera-calibration", "title": "Camera Calibration", "category": "Computer Vision", "focus": "camera calibration", "path": "skills/camera-calibration/SKILL.md"} +{"name": "edge-vision-deployment", "title": "Edge Vision Deployment", "category": "Computer Vision", "focus": "edge vision deployment", "path": "skills/edge-vision-deployment/SKILL.md"} +{"name": "vision-dataset-labeling", "title": "Vision Dataset Labeling", "category": "Computer Vision", "focus": "vision dataset labeling", "path": "skills/vision-dataset-labeling/SKILL.md"} +{"name": "vision-model-evaluation", "title": "Vision Model Evaluation", "category": "Computer Vision", "focus": "vision model evaluation", "path": "skills/vision-model-evaluation/SKILL.md"} +{"name": "visual-anomaly-detection", "title": "Visual Anomaly Detection", "category": "Computer Vision", "focus": "visual anomaly detection", "path": "skills/visual-anomaly-detection/SKILL.md"} +{"name": "speech-recognition", "title": "Speech Recognition", "category": "Speech And Audio", "focus": "speech recognition", "path": "skills/speech-recognition/SKILL.md"} +{"name": "text-to-speech", "title": "Text To Speech", "category": "Speech And Audio", "focus": "text to speech", "path": "skills/text-to-speech/SKILL.md"} +{"name": "speaker-diarization", "title": "Speaker Diarization", "category": "Speech And Audio", "focus": "speaker diarization", "path": "skills/speaker-diarization/SKILL.md"} +{"name": "speaker-verification", "title": "Speaker Verification", "category": "Speech And Audio", "focus": "speaker verification", "path": "skills/speaker-verification/SKILL.md"} +{"name": "voice-activity-detection", "title": "Voice Activity Detection", "category": "Speech And Audio", "focus": "voice activity detection", "path": "skills/voice-activity-detection/SKILL.md"} +{"name": "audio-classification", "title": "Audio Classification", "category": "Speech And Audio", "focus": "audio classification", "path": "skills/audio-classification/SKILL.md"} +{"name": "music-information-retrieval", "title": "Music Information Retrieval", "category": "Speech And Audio", "focus": "music information retrieval", "path": "skills/music-information-retrieval/SKILL.md"} +{"name": "audio-denoising", "title": "Audio Denoising", "category": "Speech And Audio", "focus": "audio denoising", "path": "skills/audio-denoising/SKILL.md"} +{"name": "source-separation", "title": "Source Separation", "category": "Speech And Audio", "focus": "source separation", "path": "skills/source-separation/SKILL.md"} +{"name": "wake-word-detection", "title": "Wake Word Detection", "category": "Speech And Audio", "focus": "wake word detection", "path": "skills/wake-word-detection/SKILL.md"} +{"name": "phoneme-alignment", "title": "Phoneme Alignment", "category": "Speech And Audio", "focus": "phoneme alignment", "path": "skills/phoneme-alignment/SKILL.md"} +{"name": "prosody-control", "title": "Prosody Control", "category": "Speech And Audio", "focus": "prosody control", "path": "skills/prosody-control/SKILL.md"} +{"name": "low-latency-streaming-asr", "title": "Low Latency Streaming ASR", "category": "Speech And Audio", "focus": "low latency streaming ASR", "path": "skills/low-latency-streaming-asr/SKILL.md"} +{"name": "accent-robustness", "title": "Accent Robustness", "category": "Speech And Audio", "focus": "accent robustness", "path": "skills/accent-robustness/SKILL.md"} +{"name": "multilingual-speech", "title": "Multilingual Speech", "category": "Speech And Audio", "focus": "multilingual speech", "path": "skills/multilingual-speech/SKILL.md"} +{"name": "audio-dataset-curation", "title": "Audio Dataset Curation", "category": "Speech And Audio", "focus": "audio dataset curation", "path": "skills/audio-dataset-curation/SKILL.md"} +{"name": "transcript-cleanup", "title": "Transcript Cleanup", "category": "Speech And Audio", "focus": "transcript cleanup", "path": "skills/transcript-cleanup/SKILL.md"} +{"name": "subtitle-generation", "title": "Subtitle Generation", "category": "Speech And Audio", "focus": "subtitle generation", "path": "skills/subtitle-generation/SKILL.md"} +{"name": "call-center-analytics", "title": "Call Center Analytics", "category": "Speech And Audio", "focus": "call center analytics", "path": "skills/call-center-analytics/SKILL.md"} +{"name": "voice-bot-integration", "title": "Voice Bot Integration", "category": "Speech And Audio", "focus": "voice bot integration", "path": "skills/voice-bot-integration/SKILL.md"} +{"name": "speech-evaluation", "title": "Speech Evaluation", "category": "Speech And Audio", "focus": "speech evaluation", "path": "skills/speech-evaluation/SKILL.md"} +{"name": "audio-feature-extraction", "title": "Audio Feature Extraction", "category": "Speech And Audio", "focus": "audio feature extraction", "path": "skills/audio-feature-extraction/SKILL.md"} +{"name": "real-time-audio-inference", "title": "Real Time Audio Inference", "category": "Speech And Audio", "focus": "real time audio inference", "path": "skills/real-time-audio-inference/SKILL.md"} +{"name": "podcast-processing", "title": "Podcast Processing", "category": "Speech And Audio", "focus": "podcast processing", "path": "skills/podcast-processing/SKILL.md"} +{"name": "voice-cloning-safeguards", "title": "Voice Cloning Safeguards", "category": "Speech And Audio", "focus": "voice cloning safeguards", "path": "skills/voice-cloning-safeguards/SKILL.md"} +{"name": "vision-language-models", "title": "Vision Language Models", "category": "Multimodal AI", "focus": "vision language models", "path": "skills/vision-language-models/SKILL.md"} +{"name": "image-grounded-chat", "title": "Image Grounded Chat", "category": "Multimodal AI", "focus": "image grounded chat", "path": "skills/image-grounded-chat/SKILL.md"} +{"name": "document-vqa", "title": "Document VQA", "category": "Multimodal AI", "focus": "document VQA", "path": "skills/document-vqa/SKILL.md"} +{"name": "chart-understanding", "title": "Chart Understanding", "category": "Multimodal AI", "focus": "chart understanding", "path": "skills/chart-understanding/SKILL.md"} +{"name": "table-understanding", "title": "Table Understanding", "category": "Multimodal AI", "focus": "table understanding", "path": "skills/table-understanding/SKILL.md"} +{"name": "video-question-answering", "title": "Video Question Answering", "category": "Multimodal AI", "focus": "video question answering", "path": "skills/video-question-answering/SKILL.md"} +{"name": "audio-visual-fusion", "title": "Audio Visual Fusion", "category": "Multimodal AI", "focus": "audio visual fusion", "path": "skills/audio-visual-fusion/SKILL.md"} +{"name": "multimodal-rag", "title": "Multimodal RAG", "category": "Multimodal AI", "focus": "multimodal RAG", "path": "skills/multimodal-rag/SKILL.md"} +{"name": "image-generation-prompting", "title": "Image Generation Prompting", "category": "Multimodal AI", "focus": "image generation prompting", "path": "skills/image-generation-prompting/SKILL.md"} +{"name": "image-editing-workflows", "title": "Image Editing Workflows", "category": "Multimodal AI", "focus": "image editing workflows", "path": "skills/image-editing-workflows/SKILL.md"} +{"name": "text-image-alignment", "title": "Text Image Alignment", "category": "Multimodal AI", "focus": "text image alignment", "path": "skills/text-image-alignment/SKILL.md"} +{"name": "cross-modal-retrieval", "title": "Cross Modal Retrieval", "category": "Multimodal AI", "focus": "cross modal retrieval", "path": "skills/cross-modal-retrieval/SKILL.md"} +{"name": "multimodal-evaluation", "title": "Multimodal Evaluation", "category": "Multimodal AI", "focus": "multimodal evaluation", "path": "skills/multimodal-evaluation/SKILL.md"} +{"name": "multimodal-safety", "title": "Multimodal Safety", "category": "Multimodal AI", "focus": "multimodal safety", "path": "skills/multimodal-safety/SKILL.md"} +{"name": "layout-aware-extraction", "title": "Layout Aware Extraction", "category": "Multimodal AI", "focus": "layout aware extraction", "path": "skills/layout-aware-extraction/SKILL.md"} +{"name": "screen-understanding", "title": "Screen Understanding", "category": "Multimodal AI", "focus": "screen understanding", "path": "skills/screen-understanding/SKILL.md"} +{"name": "ui-automation-perception", "title": "UI Automation Perception", "category": "Multimodal AI", "focus": "UI automation perception", "path": "skills/ui-automation-perception/SKILL.md"} +{"name": "robot-perception-language", "title": "Robot Perception Language", "category": "Multimodal AI", "focus": "robot perception language", "path": "skills/robot-perception-language/SKILL.md"} +{"name": "medical-multimodal-analysis", "title": "Medical Multimodal Analysis", "category": "Multimodal AI", "focus": "medical multimodal analysis", "path": "skills/medical-multimodal-analysis/SKILL.md"} +{"name": "geospatial-multimodal-analysis", "title": "Geospatial Multimodal Analysis", "category": "Multimodal AI", "focus": "geospatial multimodal analysis", "path": "skills/geospatial-multimodal-analysis/SKILL.md"} +{"name": "product-image-search", "title": "Product Image Search", "category": "Multimodal AI", "focus": "product image search", "path": "skills/product-image-search/SKILL.md"} +{"name": "visual-reasoning-tests", "title": "Visual Reasoning Tests", "category": "Multimodal AI", "focus": "visual reasoning tests", "path": "skills/visual-reasoning-tests/SKILL.md"} +{"name": "dataset-pair-generation", "title": "Dataset Pair Generation", "category": "Multimodal AI", "focus": "dataset pair generation", "path": "skills/dataset-pair-generation/SKILL.md"} +{"name": "caption-quality-review", "title": "Caption Quality Review", "category": "Multimodal AI", "focus": "caption quality review", "path": "skills/caption-quality-review/SKILL.md"} +{"name": "multimodal-latency-optimization", "title": "Multimodal Latency Optimization", "category": "Multimodal AI", "focus": "multimodal latency optimization", "path": "skills/multimodal-latency-optimization/SKILL.md"} +{"name": "etl-pipeline-design", "title": "ETL Pipeline Design", "category": "Data Engineering", "focus": "ETL pipeline design", "path": "skills/etl-pipeline-design/SKILL.md"} +{"name": "elt-pipeline-design", "title": "ELT Pipeline Design", "category": "Data Engineering", "focus": "ELT pipeline design", "path": "skills/elt-pipeline-design/SKILL.md"} +{"name": "stream-processing", "title": "Stream Processing", "category": "Data Engineering", "focus": "stream processing", "path": "skills/stream-processing/SKILL.md"} +{"name": "batch-processing", "title": "Batch Processing", "category": "Data Engineering", "focus": "batch processing", "path": "skills/batch-processing/SKILL.md"} +{"name": "data-contracts", "title": "Data Contracts", "category": "Data Engineering", "focus": "data contracts", "path": "skills/data-contracts/SKILL.md"} +{"name": "schema-evolution", "title": "Schema Evolution", "category": "Data Engineering", "focus": "schema evolution", "path": "skills/schema-evolution/SKILL.md"} +{"name": "data-quality-checks", "title": "Data Quality Checks", "category": "Data Engineering", "focus": "data quality checks", "path": "skills/data-quality-checks/SKILL.md"} +{"name": "data-lineage", "title": "Data Lineage", "category": "Data Engineering", "focus": "data lineage", "path": "skills/data-lineage/SKILL.md"} +{"name": "lakehouse-architecture", "title": "Lakehouse Architecture", "category": "Data Engineering", "focus": "lakehouse architecture", "path": "skills/lakehouse-architecture/SKILL.md"} +{"name": "warehouse-modeling", "title": "Warehouse Modeling", "category": "Data Engineering", "focus": "warehouse modeling", "path": "skills/warehouse-modeling/SKILL.md"} +{"name": "feature-stores", "title": "Feature Stores", "category": "Data Engineering", "focus": "feature stores", "path": "skills/feature-stores/SKILL.md"} +{"name": "cdc-ingestion", "title": "CDC Ingestion", "category": "Data Engineering", "focus": "CDC ingestion", "path": "skills/cdc-ingestion/SKILL.md"} +{"name": "event-tracking", "title": "Event Tracking", "category": "Data Engineering", "focus": "event tracking", "path": "skills/event-tracking/SKILL.md"} +{"name": "data-backfills", "title": "Data Backfills", "category": "Data Engineering", "focus": "data backfills", "path": "skills/data-backfills/SKILL.md"} +{"name": "idempotent-jobs", "title": "Idempotent Jobs", "category": "Data Engineering", "focus": "idempotent jobs", "path": "skills/idempotent-jobs/SKILL.md"} +{"name": "orchestration-with-dags", "title": "Orchestration With DAGs", "category": "Data Engineering", "focus": "orchestration with DAGs", "path": "skills/orchestration-with-dags/SKILL.md"} +{"name": "partitioning-strategy", "title": "Partitioning Strategy", "category": "Data Engineering", "focus": "partitioning strategy", "path": "skills/partitioning-strategy/SKILL.md"} +{"name": "incremental-models", "title": "Incremental Models", "category": "Data Engineering", "focus": "incremental models", "path": "skills/incremental-models/SKILL.md"} +{"name": "data-cataloging", "title": "Data Cataloging", "category": "Data Engineering", "focus": "data cataloging", "path": "skills/data-cataloging/SKILL.md"} +{"name": "privacy-aware-datasets", "title": "Privacy Aware Datasets", "category": "Data Engineering", "focus": "privacy aware datasets", "path": "skills/privacy-aware-datasets/SKILL.md"} +{"name": "log-analytics-pipelines", "title": "Log Analytics Pipelines", "category": "Data Engineering", "focus": "log analytics pipelines", "path": "skills/log-analytics-pipelines/SKILL.md"} +{"name": "metrics-layer-design", "title": "Metrics Layer Design", "category": "Data Engineering", "focus": "metrics layer design", "path": "skills/metrics-layer-design/SKILL.md"} +{"name": "bi-semantic-models", "title": "BI Semantic Models", "category": "Data Engineering", "focus": "BI semantic models", "path": "skills/bi-semantic-models/SKILL.md"} +{"name": "realtime-dashboards", "title": "Realtime Dashboards", "category": "Data Engineering", "focus": "realtime dashboards", "path": "skills/realtime-dashboards/SKILL.md"} +{"name": "cost-optimized-queries", "title": "Cost Optimized Queries", "category": "Data Engineering", "focus": "cost optimized queries", "path": "skills/cost-optimized-queries/SKILL.md"} +{"name": "model-registry-design", "title": "Model Registry Design", "category": "MLOps", "focus": "model registry design", "path": "skills/model-registry-design/SKILL.md"} +{"name": "experiment-tracking", "title": "Experiment Tracking", "category": "MLOps", "focus": "experiment tracking", "path": "skills/experiment-tracking/SKILL.md"} +{"name": "training-pipelines", "title": "Training Pipelines", "category": "MLOps", "focus": "training pipelines", "path": "skills/training-pipelines/SKILL.md"} +{"name": "inference-deployment", "title": "Inference Deployment", "category": "MLOps", "focus": "inference deployment", "path": "skills/inference-deployment/SKILL.md"} +{"name": "batch-inference-jobs", "title": "Batch Inference Jobs", "category": "MLOps", "focus": "batch inference jobs", "path": "skills/batch-inference-jobs/SKILL.md"} +{"name": "online-inference-services", "title": "Online Inference Services", "category": "MLOps", "focus": "online inference services", "path": "skills/online-inference-services/SKILL.md"} +{"name": "model-monitoring", "title": "Model Monitoring", "category": "MLOps", "focus": "model monitoring", "path": "skills/model-monitoring/SKILL.md"} +{"name": "drift-detection", "title": "Drift Detection", "category": "MLOps", "focus": "drift detection", "path": "skills/drift-detection/SKILL.md"} +{"name": "feature-monitoring", "title": "Feature Monitoring", "category": "MLOps", "focus": "feature monitoring", "path": "skills/feature-monitoring/SKILL.md"} +{"name": "shadow-deployments", "title": "Shadow Deployments", "category": "MLOps", "focus": "shadow deployments", "path": "skills/shadow-deployments/SKILL.md"} +{"name": "canary-releases", "title": "Canary Releases", "category": "MLOps", "focus": "canary releases", "path": "skills/canary-releases/SKILL.md"} +{"name": "a-b-testing-models", "title": "A B Testing Models", "category": "MLOps", "focus": "A B testing models", "path": "skills/a-b-testing-models/SKILL.md"} +{"name": "rollback-plans", "title": "Rollback Plans", "category": "MLOps", "focus": "rollback plans", "path": "skills/rollback-plans/SKILL.md"} +{"name": "model-cards", "title": "Model Cards", "category": "MLOps", "focus": "model cards", "path": "skills/model-cards/SKILL.md"} +{"name": "dataset-versioning", "title": "Dataset Versioning", "category": "MLOps", "focus": "dataset versioning", "path": "skills/dataset-versioning/SKILL.md"} +{"name": "reproducible-training", "title": "Reproducible Training", "category": "MLOps", "focus": "reproducible training", "path": "skills/reproducible-training/SKILL.md"} +{"name": "ci-for-ml", "title": "CI For ML", "category": "MLOps", "focus": "CI for ML", "path": "skills/ci-for-ml/SKILL.md"} +{"name": "cd-for-ml", "title": "CD For ML", "category": "MLOps", "focus": "CD for ML", "path": "skills/cd-for-ml/SKILL.md"} +{"name": "gpu-job-scheduling", "title": "GPU Job Scheduling", "category": "MLOps", "focus": "GPU job scheduling", "path": "skills/gpu-job-scheduling/SKILL.md"} +{"name": "model-serving-containers", "title": "Model Serving Containers", "category": "MLOps", "focus": "model serving containers", "path": "skills/model-serving-containers/SKILL.md"} +{"name": "edge-ml-deployment", "title": "Edge ML Deployment", "category": "MLOps", "focus": "edge ML deployment", "path": "skills/edge-ml-deployment/SKILL.md"} +{"name": "privacy-preserving-ml", "title": "Privacy Preserving ML", "category": "MLOps", "focus": "privacy preserving ML", "path": "skills/privacy-preserving-ml/SKILL.md"} +{"name": "federated-learning-operations", "title": "Federated Learning Operations", "category": "MLOps", "focus": "federated learning operations", "path": "skills/federated-learning-operations/SKILL.md"} +{"name": "compliance-evidence", "title": "Compliance Evidence", "category": "MLOps", "focus": "compliance evidence", "path": "skills/compliance-evidence/SKILL.md"} +{"name": "incident-runbooks", "title": "Incident Runbooks", "category": "MLOps", "focus": "incident runbooks", "path": "skills/incident-runbooks/SKILL.md"} +{"name": "react-application-architecture", "title": "React Application Architecture", "category": "Web Engineering", "focus": "React application architecture", "path": "skills/react-application-architecture/SKILL.md"} +{"name": "next-js-application-architecture", "title": "Next.js Application Architecture", "category": "Web Engineering", "focus": "Next.js application architecture", "path": "skills/next-js-application-architecture/SKILL.md"} +{"name": "vue-application-architecture", "title": "Vue Application Architecture", "category": "Web Engineering", "focus": "Vue application architecture", "path": "skills/vue-application-architecture/SKILL.md"} +{"name": "svelte-application-architecture", "title": "Svelte Application Architecture", "category": "Web Engineering", "focus": "Svelte application architecture", "path": "skills/svelte-application-architecture/SKILL.md"} +{"name": "api-route-design", "title": "API Route Design", "category": "Web Engineering", "focus": "API route design", "path": "skills/api-route-design/SKILL.md"} +{"name": "server-side-rendering", "title": "Server Side Rendering", "category": "Web Engineering", "focus": "server side rendering", "path": "skills/server-side-rendering/SKILL.md"} +{"name": "static-site-generation", "title": "Static Site Generation", "category": "Web Engineering", "focus": "static site generation", "path": "skills/static-site-generation/SKILL.md"} +{"name": "web-accessibility", "title": "Web Accessibility", "category": "Web Engineering", "focus": "web accessibility", "path": "skills/web-accessibility/SKILL.md"} +{"name": "responsive-ui-systems", "title": "Responsive UI Systems", "category": "Web Engineering", "focus": "responsive UI systems", "path": "skills/responsive-ui-systems/SKILL.md"} +{"name": "design-system-components", "title": "Design System Components", "category": "Web Engineering", "focus": "design system components", "path": "skills/design-system-components/SKILL.md"} +{"name": "state-management", "title": "State Management", "category": "Web Engineering", "focus": "state management", "path": "skills/state-management/SKILL.md"} +{"name": "form-validation", "title": "Form Validation", "category": "Web Engineering", "focus": "form validation", "path": "skills/form-validation/SKILL.md"} +{"name": "authentication-flows", "title": "Authentication Flows", "category": "Web Engineering", "focus": "authentication flows", "path": "skills/authentication-flows/SKILL.md"} +{"name": "authorization-ui", "title": "Authorization UI", "category": "Web Engineering", "focus": "authorization UI", "path": "skills/authorization-ui/SKILL.md"} +{"name": "web-performance", "title": "Web Performance", "category": "Web Engineering", "focus": "web performance", "path": "skills/web-performance/SKILL.md"} +{"name": "browser-testing", "title": "Browser Testing", "category": "Web Engineering", "focus": "browser testing", "path": "skills/browser-testing/SKILL.md"} +{"name": "frontend-error-monitoring", "title": "Frontend Error Monitoring", "category": "Web Engineering", "focus": "frontend error monitoring", "path": "skills/frontend-error-monitoring/SKILL.md"} +{"name": "progressive-web-apps", "title": "Progressive Web Apps", "category": "Web Engineering", "focus": "progressive web apps", "path": "skills/progressive-web-apps/SKILL.md"} +{"name": "websocket-features", "title": "Websocket Features", "category": "Web Engineering", "focus": "websocket features", "path": "skills/websocket-features/SKILL.md"} +{"name": "file-upload-interfaces", "title": "File Upload Interfaces", "category": "Web Engineering", "focus": "file upload interfaces", "path": "skills/file-upload-interfaces/SKILL.md"} +{"name": "admin-dashboards", "title": "Admin Dashboards", "category": "Web Engineering", "focus": "admin dashboards", "path": "skills/admin-dashboards/SKILL.md"} +{"name": "data-visualization-ui", "title": "Data Visualization UI", "category": "Web Engineering", "focus": "data visualization UI", "path": "skills/data-visualization-ui/SKILL.md"} +{"name": "internationalization", "title": "Internationalization", "category": "Web Engineering", "focus": "internationalization", "path": "skills/internationalization/SKILL.md"} +{"name": "seo-technical-checks", "title": "SEO Technical Checks", "category": "Web Engineering", "focus": "SEO technical checks", "path": "skills/seo-technical-checks/SKILL.md"} +{"name": "web-security-headers", "title": "Web Security Headers", "category": "Web Engineering", "focus": "web security headers", "path": "skills/web-security-headers/SKILL.md"} +{"name": "react-native-apps", "title": "React Native Apps", "category": "Mobile App Engineering", "focus": "React Native apps", "path": "skills/react-native-apps/SKILL.md"} +{"name": "flutter-apps", "title": "Flutter Apps", "category": "Mobile App Engineering", "focus": "Flutter apps", "path": "skills/flutter-apps/SKILL.md"} +{"name": "ios-swift-apps", "title": "IOS Swift Apps", "category": "Mobile App Engineering", "focus": "iOS Swift apps", "path": "skills/ios-swift-apps/SKILL.md"} +{"name": "android-kotlin-apps", "title": "Android Kotlin Apps", "category": "Mobile App Engineering", "focus": "Android Kotlin apps", "path": "skills/android-kotlin-apps/SKILL.md"} +{"name": "mobile-navigation", "title": "Mobile Navigation", "category": "Mobile App Engineering", "focus": "mobile navigation", "path": "skills/mobile-navigation/SKILL.md"} +{"name": "offline-first-mobile", "title": "Offline First Mobile", "category": "Mobile App Engineering", "focus": "offline first mobile", "path": "skills/offline-first-mobile/SKILL.md"} +{"name": "push-notifications", "title": "Push Notifications", "category": "Mobile App Engineering", "focus": "push notifications", "path": "skills/push-notifications/SKILL.md"} +{"name": "mobile-authentication", "title": "Mobile Authentication", "category": "Mobile App Engineering", "focus": "mobile authentication", "path": "skills/mobile-authentication/SKILL.md"} +{"name": "in-app-purchases", "title": "In App Purchases", "category": "Mobile App Engineering", "focus": "in app purchases", "path": "skills/in-app-purchases/SKILL.md"} +{"name": "mobile-analytics", "title": "Mobile Analytics", "category": "Mobile App Engineering", "focus": "mobile analytics", "path": "skills/mobile-analytics/SKILL.md"} +{"name": "mobile-accessibility", "title": "Mobile Accessibility", "category": "Mobile App Engineering", "focus": "mobile accessibility", "path": "skills/mobile-accessibility/SKILL.md"} +{"name": "app-store-readiness", "title": "App Store Readiness", "category": "Mobile App Engineering", "focus": "app store readiness", "path": "skills/app-store-readiness/SKILL.md"} +{"name": "device-permissions", "title": "Device Permissions", "category": "Mobile App Engineering", "focus": "device permissions", "path": "skills/device-permissions/SKILL.md"} +{"name": "camera-integrations", "title": "Camera Integrations", "category": "Mobile App Engineering", "focus": "camera integrations", "path": "skills/camera-integrations/SKILL.md"} +{"name": "location-features", "title": "Location Features", "category": "Mobile App Engineering", "focus": "location features", "path": "skills/location-features/SKILL.md"} +{"name": "background-sync", "title": "Background Sync", "category": "Mobile App Engineering", "focus": "background sync", "path": "skills/background-sync/SKILL.md"} +{"name": "mobile-performance", "title": "Mobile Performance", "category": "Mobile App Engineering", "focus": "mobile performance", "path": "skills/mobile-performance/SKILL.md"} +{"name": "crash-reporting", "title": "Crash Reporting", "category": "Mobile App Engineering", "focus": "crash reporting", "path": "skills/crash-reporting/SKILL.md"} +{"name": "mobile-test-automation", "title": "Mobile Test Automation", "category": "Mobile App Engineering", "focus": "mobile test automation", "path": "skills/mobile-test-automation/SKILL.md"} +{"name": "responsive-tablet-layouts", "title": "Responsive Tablet Layouts", "category": "Mobile App Engineering", "focus": "responsive tablet layouts", "path": "skills/responsive-tablet-layouts/SKILL.md"} +{"name": "secure-local-storage", "title": "Secure Local Storage", "category": "Mobile App Engineering", "focus": "secure local storage", "path": "skills/secure-local-storage/SKILL.md"} +{"name": "deep-linking", "title": "Deep Linking", "category": "Mobile App Engineering", "focus": "deep linking", "path": "skills/deep-linking/SKILL.md"} +{"name": "mobile-onboarding", "title": "Mobile Onboarding", "category": "Mobile App Engineering", "focus": "mobile onboarding", "path": "skills/mobile-onboarding/SKILL.md"} +{"name": "cross-platform-design-systems", "title": "Cross Platform Design Systems", "category": "Mobile App Engineering", "focus": "cross platform design systems", "path": "skills/cross-platform-design-systems/SKILL.md"} +{"name": "mobile-release-pipelines", "title": "Mobile Release Pipelines", "category": "Mobile App Engineering", "focus": "mobile release pipelines", "path": "skills/mobile-release-pipelines/SKILL.md"} +{"name": "docker-packaging", "title": "Docker Packaging", "category": "Cloud And DevOps", "focus": "Docker packaging", "path": "skills/docker-packaging/SKILL.md"} +{"name": "kubernetes-deployments", "title": "Kubernetes Deployments", "category": "Cloud And DevOps", "focus": "Kubernetes deployments", "path": "skills/kubernetes-deployments/SKILL.md"} +{"name": "serverless-functions", "title": "Serverless Functions", "category": "Cloud And DevOps", "focus": "serverless functions", "path": "skills/serverless-functions/SKILL.md"} +{"name": "container-registries", "title": "Container Registries", "category": "Cloud And DevOps", "focus": "container registries", "path": "skills/container-registries/SKILL.md"} +{"name": "infrastructure-as-code", "title": "Infrastructure As Code", "category": "Cloud And DevOps", "focus": "infrastructure as code", "path": "skills/infrastructure-as-code/SKILL.md"} +{"name": "terraform-modules", "title": "Terraform Modules", "category": "Cloud And DevOps", "focus": "Terraform modules", "path": "skills/terraform-modules/SKILL.md"} +{"name": "cloud-cost-optimization", "title": "Cloud Cost Optimization", "category": "Cloud And DevOps", "focus": "cloud cost optimization", "path": "skills/cloud-cost-optimization/SKILL.md"} +{"name": "autoscaling-design", "title": "Autoscaling Design", "category": "Cloud And DevOps", "focus": "autoscaling design", "path": "skills/autoscaling-design/SKILL.md"} +{"name": "load-balancer-setup", "title": "Load Balancer Setup", "category": "Cloud And DevOps", "focus": "load balancer setup", "path": "skills/load-balancer-setup/SKILL.md"} +{"name": "cdn-configuration", "title": "CDN Configuration", "category": "Cloud And DevOps", "focus": "CDN configuration", "path": "skills/cdn-configuration/SKILL.md"} +{"name": "secrets-management", "title": "Secrets Management", "category": "Cloud And DevOps", "focus": "secrets management", "path": "skills/secrets-management/SKILL.md"} +{"name": "observability-stacks", "title": "Observability Stacks", "category": "Cloud And DevOps", "focus": "observability stacks", "path": "skills/observability-stacks/SKILL.md"} +{"name": "logging-pipelines", "title": "Logging Pipelines", "category": "Cloud And DevOps", "focus": "logging pipelines", "path": "skills/logging-pipelines/SKILL.md"} +{"name": "metrics-alerts", "title": "Metrics Alerts", "category": "Cloud And DevOps", "focus": "metrics alerts", "path": "skills/metrics-alerts/SKILL.md"} +{"name": "incident-response", "title": "Incident Response", "category": "Cloud And DevOps", "focus": "incident response", "path": "skills/incident-response/SKILL.md"} +{"name": "backup-and-restore", "title": "Backup and Restore", "category": "Cloud And DevOps", "focus": "backup and restore", "path": "skills/backup-and-restore/SKILL.md"} +{"name": "zero-downtime-deploys", "title": "Zero Downtime Deploys", "category": "Cloud And DevOps", "focus": "zero downtime deploys", "path": "skills/zero-downtime-deploys/SKILL.md"} +{"name": "blue-green-deploys", "title": "Blue Green Deploys", "category": "Cloud And DevOps", "focus": "blue green deploys", "path": "skills/blue-green-deploys/SKILL.md"} +{"name": "networking-design", "title": "Networking Design", "category": "Cloud And DevOps", "focus": "networking design", "path": "skills/networking-design/SKILL.md"} +{"name": "iam-policy-design", "title": "IAM Policy Design", "category": "Cloud And DevOps", "focus": "IAM policy design", "path": "skills/iam-policy-design/SKILL.md"} +{"name": "multi-environment-config", "title": "Multi Environment Config", "category": "Cloud And DevOps", "focus": "multi environment config", "path": "skills/multi-environment-config/SKILL.md"} +{"name": "ci-pipeline-design", "title": "CI Pipeline Design", "category": "Cloud And DevOps", "focus": "CI pipeline design", "path": "skills/ci-pipeline-design/SKILL.md"} +{"name": "artifact-promotion", "title": "Artifact Promotion", "category": "Cloud And DevOps", "focus": "artifact promotion", "path": "skills/artifact-promotion/SKILL.md"} +{"name": "database-migrations", "title": "Database Migrations", "category": "Cloud And DevOps", "focus": "database migrations", "path": "skills/database-migrations/SKILL.md"} +{"name": "disaster-recovery", "title": "Disaster Recovery", "category": "Cloud And DevOps", "focus": "disaster recovery", "path": "skills/disaster-recovery/SKILL.md"} +{"name": "threat-modeling", "title": "Threat Modeling", "category": "Security And Privacy", "focus": "threat modeling", "path": "skills/threat-modeling/SKILL.md"} +{"name": "secure-code-review", "title": "Secure Code Review", "category": "Security And Privacy", "focus": "secure code review", "path": "skills/secure-code-review/SKILL.md"} +{"name": "dependency-vulnerability-handling", "title": "Dependency Vulnerability Handling", "category": "Security And Privacy", "focus": "dependency vulnerability handling", "path": "skills/dependency-vulnerability-handling/SKILL.md"} +{"name": "secret-scanning", "title": "Secret Scanning", "category": "Security And Privacy", "focus": "secret scanning", "path": "skills/secret-scanning/SKILL.md"} +{"name": "authentication-security", "title": "Authentication Security", "category": "Security And Privacy", "focus": "authentication security", "path": "skills/authentication-security/SKILL.md"} +{"name": "authorization-security", "title": "Authorization Security", "category": "Security And Privacy", "focus": "authorization security", "path": "skills/authorization-security/SKILL.md"} +{"name": "oauth-integration", "title": "OAuth Integration", "category": "Security And Privacy", "focus": "OAuth integration", "path": "skills/oauth-integration/SKILL.md"} +{"name": "jwt-handling", "title": "JWT Handling", "category": "Security And Privacy", "focus": "JWT handling", "path": "skills/jwt-handling/SKILL.md"} +{"name": "api-abuse-prevention", "title": "API Abuse Prevention", "category": "Security And Privacy", "focus": "API abuse prevention", "path": "skills/api-abuse-prevention/SKILL.md"} +{"name": "rate-limiting", "title": "Rate Limiting", "category": "Security And Privacy", "focus": "rate limiting", "path": "skills/rate-limiting/SKILL.md"} +{"name": "input-validation", "title": "Input Validation", "category": "Security And Privacy", "focus": "input validation", "path": "skills/input-validation/SKILL.md"} +{"name": "sql-injection-prevention", "title": "SQL Injection Prevention", "category": "Security And Privacy", "focus": "SQL injection prevention", "path": "skills/sql-injection-prevention/SKILL.md"} +{"name": "xss-prevention", "title": "XSS Prevention", "category": "Security And Privacy", "focus": "XSS prevention", "path": "skills/xss-prevention/SKILL.md"} +{"name": "csrf-prevention", "title": "CSRF Prevention", "category": "Security And Privacy", "focus": "CSRF prevention", "path": "skills/csrf-prevention/SKILL.md"} +{"name": "data-encryption", "title": "Data Encryption", "category": "Security And Privacy", "focus": "data encryption", "path": "skills/data-encryption/SKILL.md"} +{"name": "key-rotation", "title": "Key Rotation", "category": "Security And Privacy", "focus": "key rotation", "path": "skills/key-rotation/SKILL.md"} +{"name": "privacy-impact-review", "title": "Privacy Impact Review", "category": "Security And Privacy", "focus": "privacy impact review", "path": "skills/privacy-impact-review/SKILL.md"} +{"name": "pii-minimization", "title": "PII Minimization", "category": "Security And Privacy", "focus": "PII minimization", "path": "skills/pii-minimization/SKILL.md"} +{"name": "audit-logging", "title": "Audit Logging", "category": "Security And Privacy", "focus": "audit logging", "path": "skills/audit-logging/SKILL.md"} +{"name": "security-monitoring", "title": "Security Monitoring", "category": "Security And Privacy", "focus": "security monitoring", "path": "skills/security-monitoring/SKILL.md"} +{"name": "penetration-test-triage", "title": "Penetration Test Triage", "category": "Security And Privacy", "focus": "penetration test triage", "path": "skills/penetration-test-triage/SKILL.md"} +{"name": "supply-chain-security", "title": "Supply Chain Security", "category": "Security And Privacy", "focus": "supply chain security", "path": "skills/supply-chain-security/SKILL.md"} +{"name": "sandboxed-execution", "title": "Sandboxed Execution", "category": "Security And Privacy", "focus": "sandboxed execution", "path": "skills/sandboxed-execution/SKILL.md"} +{"name": "ai-safety-policy", "title": "AI Safety Policy", "category": "Security And Privacy", "focus": "AI safety policy", "path": "skills/ai-safety-policy/SKILL.md"} +{"name": "red-team-planning", "title": "Red Team Planning", "category": "Security And Privacy", "focus": "red team planning", "path": "skills/red-team-planning/SKILL.md"} +{"name": "postgresql-schema-design", "title": "PostgreSQL Schema Design", "category": "Databases And Analytics", "focus": "PostgreSQL schema design", "path": "skills/postgresql-schema-design/SKILL.md"} +{"name": "mysql-query-optimization", "title": "MySQL Query Optimization", "category": "Databases And Analytics", "focus": "MySQL query optimization", "path": "skills/mysql-query-optimization/SKILL.md"} +{"name": "sqlite-embedded-storage", "title": "SQLite Embedded Storage", "category": "Databases And Analytics", "focus": "SQLite embedded storage", "path": "skills/sqlite-embedded-storage/SKILL.md"} +{"name": "mongodb-document-modeling", "title": "MongoDB Document Modeling", "category": "Databases And Analytics", "focus": "MongoDB document modeling", "path": "skills/mongodb-document-modeling/SKILL.md"} +{"name": "redis-caching", "title": "Redis Caching", "category": "Databases And Analytics", "focus": "Redis caching", "path": "skills/redis-caching/SKILL.md"} +{"name": "elasticsearch-search-design", "title": "Elasticsearch Search Design", "category": "Databases And Analytics", "focus": "Elasticsearch search design", "path": "skills/elasticsearch-search-design/SKILL.md"} +{"name": "vector-database-design", "title": "Vector Database Design", "category": "Databases And Analytics", "focus": "vector database design", "path": "skills/vector-database-design/SKILL.md"} +{"name": "graph-database-modeling", "title": "Graph Database Modeling", "category": "Databases And Analytics", "focus": "graph database modeling", "path": "skills/graph-database-modeling/SKILL.md"} +{"name": "time-series-databases", "title": "Time Series Databases", "category": "Databases And Analytics", "focus": "time series databases", "path": "skills/time-series-databases/SKILL.md"} +{"name": "olap-cube-modeling", "title": "OLAP Cube Modeling", "category": "Databases And Analytics", "focus": "OLAP cube modeling", "path": "skills/olap-cube-modeling/SKILL.md"} +{"name": "index-tuning", "title": "Index Tuning", "category": "Databases And Analytics", "focus": "index tuning", "path": "skills/index-tuning/SKILL.md"} +{"name": "query-plan-analysis", "title": "Query Plan Analysis", "category": "Databases And Analytics", "focus": "query plan analysis", "path": "skills/query-plan-analysis/SKILL.md"} +{"name": "migration-planning", "title": "Migration Planning", "category": "Databases And Analytics", "focus": "migration planning", "path": "skills/migration-planning/SKILL.md"} +{"name": "multi-tenant-data-models", "title": "Multi Tenant Data Models", "category": "Databases And Analytics", "focus": "multi tenant data models", "path": "skills/multi-tenant-data-models/SKILL.md"} +{"name": "transaction-design", "title": "Transaction Design", "category": "Databases And Analytics", "focus": "transaction design", "path": "skills/transaction-design/SKILL.md"} +{"name": "replication-strategy", "title": "Replication Strategy", "category": "Databases And Analytics", "focus": "replication strategy", "path": "skills/replication-strategy/SKILL.md"} +{"name": "backup-verification", "title": "Backup Verification", "category": "Databases And Analytics", "focus": "backup verification", "path": "skills/backup-verification/SKILL.md"} +{"name": "analytics-event-schemas", "title": "Analytics Event Schemas", "category": "Databases And Analytics", "focus": "analytics event schemas", "path": "skills/analytics-event-schemas/SKILL.md"} +{"name": "dashboard-metric-definitions", "title": "Dashboard Metric Definitions", "category": "Databases And Analytics", "focus": "dashboard metric definitions", "path": "skills/dashboard-metric-definitions/SKILL.md"} +{"name": "cohort-analysis", "title": "Cohort Analysis", "category": "Databases And Analytics", "focus": "cohort analysis", "path": "skills/cohort-analysis/SKILL.md"} +{"name": "funnel-analysis", "title": "Funnel Analysis", "category": "Databases And Analytics", "focus": "funnel analysis", "path": "skills/funnel-analysis/SKILL.md"} +{"name": "retention-analysis", "title": "Retention Analysis", "category": "Databases And Analytics", "focus": "retention analysis", "path": "skills/retention-analysis/SKILL.md"} +{"name": "data-warehouse-sql", "title": "Data Warehouse SQL", "category": "Databases And Analytics", "focus": "data warehouse SQL", "path": "skills/data-warehouse-sql/SKILL.md"} +{"name": "dbt-model-design", "title": "DBT Model Design", "category": "Databases And Analytics", "focus": "dbt model design", "path": "skills/dbt-model-design/SKILL.md"} +{"name": "governed-self-service-analytics", "title": "Governed Self Service Analytics", "category": "Databases And Analytics", "focus": "governed self service analytics", "path": "skills/governed-self-service-analytics/SKILL.md"} +{"name": "ai-feature-scoping", "title": "AI Feature Scoping", "category": "AI Product And UX", "focus": "AI feature scoping", "path": "skills/ai-feature-scoping/SKILL.md"} +{"name": "ai-user-onboarding", "title": "AI User Onboarding", "category": "AI Product And UX", "focus": "AI user onboarding", "path": "skills/ai-user-onboarding/SKILL.md"} +{"name": "chat-ux-design", "title": "Chat UX Design", "category": "AI Product And UX", "focus": "chat UX design", "path": "skills/chat-ux-design/SKILL.md"} +{"name": "ai-disclosure-copy", "title": "AI Disclosure Copy", "category": "AI Product And UX", "focus": "AI disclosure copy", "path": "skills/ai-disclosure-copy/SKILL.md"} +{"name": "confidence-display", "title": "Confidence Display", "category": "AI Product And UX", "focus": "confidence display", "path": "skills/confidence-display/SKILL.md"} +{"name": "human-review-queues", "title": "Human Review Queues", "category": "AI Product And UX", "focus": "human review queues", "path": "skills/human-review-queues/SKILL.md"} +{"name": "feedback-collection", "title": "Feedback Collection", "category": "AI Product And UX", "focus": "feedback collection", "path": "skills/feedback-collection/SKILL.md"} +{"name": "explainable-ai-ux", "title": "Explainable AI UX", "category": "AI Product And UX", "focus": "explainable AI UX", "path": "skills/explainable-ai-ux/SKILL.md"} +{"name": "error-recovery-flows", "title": "Error Recovery Flows", "category": "AI Product And UX", "focus": "error recovery flows", "path": "skills/error-recovery-flows/SKILL.md"} +{"name": "user-trust-signals", "title": "User Trust Signals", "category": "AI Product And UX", "focus": "user trust signals", "path": "skills/user-trust-signals/SKILL.md"} +{"name": "ai-settings-panels", "title": "AI Settings Panels", "category": "AI Product And UX", "focus": "AI settings panels", "path": "skills/ai-settings-panels/SKILL.md"} +{"name": "model-choice-ux", "title": "Model Choice UX", "category": "AI Product And UX", "focus": "model choice UX", "path": "skills/model-choice-ux/SKILL.md"} +{"name": "prompt-library-ux", "title": "Prompt Library UX", "category": "AI Product And UX", "focus": "prompt library UX", "path": "skills/prompt-library-ux/SKILL.md"} +{"name": "workflow-automation-ux", "title": "Workflow Automation UX", "category": "AI Product And UX", "focus": "workflow automation UX", "path": "skills/workflow-automation-ux/SKILL.md"} +{"name": "ai-admin-controls", "title": "AI Admin Controls", "category": "AI Product And UX", "focus": "AI admin controls", "path": "skills/ai-admin-controls/SKILL.md"} +{"name": "usage-metering-ux", "title": "Usage Metering UX", "category": "AI Product And UX", "focus": "usage metering UX", "path": "skills/usage-metering-ux/SKILL.md"} +{"name": "enterprise-permission-ux", "title": "Enterprise Permission UX", "category": "AI Product And UX", "focus": "enterprise permission UX", "path": "skills/enterprise-permission-ux/SKILL.md"} +{"name": "evaluation-dashboards", "title": "Evaluation Dashboards", "category": "AI Product And UX", "focus": "evaluation dashboards", "path": "skills/evaluation-dashboards/SKILL.md"} +{"name": "annotation-workflows", "title": "Annotation Workflows", "category": "AI Product And UX", "focus": "annotation workflows", "path": "skills/annotation-workflows/SKILL.md"} +{"name": "customer-support-ai-ux", "title": "Customer Support AI UX", "category": "AI Product And UX", "focus": "customer support AI UX", "path": "skills/customer-support-ai-ux/SKILL.md"} +{"name": "search-assistant-ux", "title": "Search Assistant UX", "category": "AI Product And UX", "focus": "search assistant UX", "path": "skills/search-assistant-ux/SKILL.md"} +{"name": "creative-generation-ux", "title": "Creative Generation UX", "category": "AI Product And UX", "focus": "creative generation UX", "path": "skills/creative-generation-ux/SKILL.md"} +{"name": "ai-productivity-tools", "title": "AI Productivity Tools", "category": "AI Product And UX", "focus": "AI productivity tools", "path": "skills/ai-productivity-tools/SKILL.md"} +{"name": "ai-collaboration-features", "title": "AI Collaboration Features", "category": "AI Product And UX", "focus": "AI collaboration features", "path": "skills/ai-collaboration-features/SKILL.md"} +{"name": "accessibility-for-ai-products", "title": "Accessibility For AI Products", "category": "AI Product And UX", "focus": "accessibility for AI products", "path": "skills/accessibility-for-ai-products/SKILL.md"} +{"name": "robot-motion-planning", "title": "Robot Motion Planning", "category": "Robotics And IoT", "focus": "robot motion planning", "path": "skills/robot-motion-planning/SKILL.md"} +{"name": "robot-perception", "title": "Robot Perception", "category": "Robotics And IoT", "focus": "robot perception", "path": "skills/robot-perception/SKILL.md"} +{"name": "ros-integration", "title": "ROS Integration", "category": "Robotics And IoT", "focus": "ROS integration", "path": "skills/ros-integration/SKILL.md"} +{"name": "sensor-fusion", "title": "Sensor Fusion", "category": "Robotics And IoT", "focus": "sensor fusion", "path": "skills/sensor-fusion/SKILL.md"} +{"name": "slam-workflows", "title": "SLAM Workflows", "category": "Robotics And IoT", "focus": "SLAM workflows", "path": "skills/slam-workflows/SKILL.md"} +{"name": "path-planning", "title": "Path Planning", "category": "Robotics And IoT", "focus": "path planning", "path": "skills/path-planning/SKILL.md"} +{"name": "control-systems", "title": "Control Systems", "category": "Robotics And IoT", "focus": "control systems", "path": "skills/control-systems/SKILL.md"} +{"name": "edge-inference-devices", "title": "Edge Inference Devices", "category": "Robotics And IoT", "focus": "edge inference devices", "path": "skills/edge-inference-devices/SKILL.md"} +{"name": "iot-telemetry-ingestion", "title": "IOT Telemetry Ingestion", "category": "Robotics And IoT", "focus": "IoT telemetry ingestion", "path": "skills/iot-telemetry-ingestion/SKILL.md"} +{"name": "device-provisioning", "title": "Device Provisioning", "category": "Robotics And IoT", "focus": "device provisioning", "path": "skills/device-provisioning/SKILL.md"} +{"name": "firmware-update-workflows", "title": "Firmware Update Workflows", "category": "Robotics And IoT", "focus": "firmware update workflows", "path": "skills/firmware-update-workflows/SKILL.md"} +{"name": "digital-twins", "title": "Digital Twins", "category": "Robotics And IoT", "focus": "digital twins", "path": "skills/digital-twins/SKILL.md"} +{"name": "predictive-maintenance", "title": "Predictive Maintenance", "category": "Robotics And IoT", "focus": "predictive maintenance", "path": "skills/predictive-maintenance/SKILL.md"} +{"name": "industrial-vision", "title": "Industrial Vision", "category": "Robotics And IoT", "focus": "industrial vision", "path": "skills/industrial-vision/SKILL.md"} +{"name": "autonomous-navigation", "title": "Autonomous Navigation", "category": "Robotics And IoT", "focus": "autonomous navigation", "path": "skills/autonomous-navigation/SKILL.md"} +{"name": "robot-simulation", "title": "Robot Simulation", "category": "Robotics And IoT", "focus": "robot simulation", "path": "skills/robot-simulation/SKILL.md"} +{"name": "hardware-in-the-loop-tests", "title": "Hardware In The Loop Tests", "category": "Robotics And IoT", "focus": "hardware in the loop tests", "path": "skills/hardware-in-the-loop-tests/SKILL.md"} +{"name": "low-power-ml", "title": "Low Power ML", "category": "Robotics And IoT", "focus": "low power ML", "path": "skills/low-power-ml/SKILL.md"} +{"name": "embedded-linux", "title": "Embedded Linux", "category": "Robotics And IoT", "focus": "embedded Linux", "path": "skills/embedded-linux/SKILL.md"} +{"name": "microcontroller-inference", "title": "Microcontroller Inference", "category": "Robotics And IoT", "focus": "microcontroller inference", "path": "skills/microcontroller-inference/SKILL.md"} +{"name": "mqtt-architectures", "title": "MQTT Architectures", "category": "Robotics And IoT", "focus": "MQTT architectures", "path": "skills/mqtt-architectures/SKILL.md"} +{"name": "fleet-monitoring", "title": "Fleet Monitoring", "category": "Robotics And IoT", "focus": "fleet monitoring", "path": "skills/fleet-monitoring/SKILL.md"} +{"name": "factory-automation", "title": "Factory Automation", "category": "Robotics And IoT", "focus": "factory automation", "path": "skills/factory-automation/SKILL.md"} +{"name": "warehouse-robotics", "title": "Warehouse Robotics", "category": "Robotics And IoT", "focus": "warehouse robotics", "path": "skills/warehouse-robotics/SKILL.md"} +{"name": "safety-interlocks", "title": "Safety Interlocks", "category": "Robotics And IoT", "focus": "safety interlocks", "path": "skills/safety-interlocks/SKILL.md"} +{"name": "healthcare-ai-workflows", "title": "Healthcare AI Workflows", "category": "Domain AI", "focus": "healthcare AI workflows", "path": "skills/healthcare-ai-workflows/SKILL.md"} +{"name": "finance-ai-workflows", "title": "Finance AI Workflows", "category": "Domain AI", "focus": "finance AI workflows", "path": "skills/finance-ai-workflows/SKILL.md"} +{"name": "legal-ai-workflows", "title": "Legal AI Workflows", "category": "Domain AI", "focus": "legal AI workflows", "path": "skills/legal-ai-workflows/SKILL.md"} +{"name": "education-ai-workflows", "title": "Education AI Workflows", "category": "Domain AI", "focus": "education AI workflows", "path": "skills/education-ai-workflows/SKILL.md"} +{"name": "retail-ai-workflows", "title": "Retail AI Workflows", "category": "Domain AI", "focus": "retail AI workflows", "path": "skills/retail-ai-workflows/SKILL.md"} +{"name": "marketing-ai-workflows", "title": "Marketing AI Workflows", "category": "Domain AI", "focus": "marketing AI workflows", "path": "skills/marketing-ai-workflows/SKILL.md"} +{"name": "sales-ai-workflows", "title": "Sales AI Workflows", "category": "Domain AI", "focus": "sales AI workflows", "path": "skills/sales-ai-workflows/SKILL.md"} +{"name": "hr-ai-workflows", "title": "HR AI Workflows", "category": "Domain AI", "focus": "HR AI workflows", "path": "skills/hr-ai-workflows/SKILL.md"} +{"name": "insurance-ai-workflows", "title": "Insurance AI Workflows", "category": "Domain AI", "focus": "insurance AI workflows", "path": "skills/insurance-ai-workflows/SKILL.md"} +{"name": "real-estate-ai-workflows", "title": "Real Estate AI Workflows", "category": "Domain AI", "focus": "real estate AI workflows", "path": "skills/real-estate-ai-workflows/SKILL.md"} +{"name": "manufacturing-ai-workflows", "title": "Manufacturing AI Workflows", "category": "Domain AI", "focus": "manufacturing AI workflows", "path": "skills/manufacturing-ai-workflows/SKILL.md"} +{"name": "logistics-ai-workflows", "title": "Logistics AI Workflows", "category": "Domain AI", "focus": "logistics AI workflows", "path": "skills/logistics-ai-workflows/SKILL.md"} +{"name": "energy-ai-workflows", "title": "Energy AI Workflows", "category": "Domain AI", "focus": "energy AI workflows", "path": "skills/energy-ai-workflows/SKILL.md"} +{"name": "agriculture-ai-workflows", "title": "Agriculture AI Workflows", "category": "Domain AI", "focus": "agriculture AI workflows", "path": "skills/agriculture-ai-workflows/SKILL.md"} +{"name": "public-sector-ai-workflows", "title": "Public Sector AI Workflows", "category": "Domain AI", "focus": "public sector AI workflows", "path": "skills/public-sector-ai-workflows/SKILL.md"} +{"name": "media-ai-workflows", "title": "Media AI Workflows", "category": "Domain AI", "focus": "media AI workflows", "path": "skills/media-ai-workflows/SKILL.md"} +{"name": "gaming-ai-workflows", "title": "Gaming AI Workflows", "category": "Domain AI", "focus": "gaming AI workflows", "path": "skills/gaming-ai-workflows/SKILL.md"} +{"name": "cybersecurity-ai-workflows", "title": "Cybersecurity AI Workflows", "category": "Domain AI", "focus": "cybersecurity AI workflows", "path": "skills/cybersecurity-ai-workflows/SKILL.md"} +{"name": "scientific-literature-ai", "title": "Scientific Literature AI", "category": "Domain AI", "focus": "scientific literature AI", "path": "skills/scientific-literature-ai/SKILL.md"} +{"name": "customer-service-ai", "title": "Customer Service AI", "category": "Domain AI", "focus": "customer service AI", "path": "skills/customer-service-ai/SKILL.md"} +{"name": "knowledge-management-ai", "title": "Knowledge Management AI", "category": "Domain AI", "focus": "knowledge management AI", "path": "skills/knowledge-management-ai/SKILL.md"} +{"name": "procurement-ai", "title": "Procurement AI", "category": "Domain AI", "focus": "procurement AI", "path": "skills/procurement-ai/SKILL.md"} +{"name": "supply-chain-ai", "title": "Supply Chain AI", "category": "Domain AI", "focus": "supply chain AI", "path": "skills/supply-chain-ai/SKILL.md"} +{"name": "compliance-ai", "title": "Compliance AI", "category": "Domain AI", "focus": "compliance AI", "path": "skills/compliance-ai/SKILL.md"} +{"name": "personal-productivity-ai", "title": "Personal Productivity AI", "category": "Domain AI", "focus": "personal productivity AI", "path": "skills/personal-productivity-ai/SKILL.md"} +{"name": "paper-reproduction", "title": "Paper Reproduction", "category": "Research And Scientific AI", "focus": "paper reproduction", "path": "skills/paper-reproduction/SKILL.md"} +{"name": "benchmark-suite-design", "title": "Benchmark Suite Design", "category": "Research And Scientific AI", "focus": "benchmark suite design", "path": "skills/benchmark-suite-design/SKILL.md"} +{"name": "ablation-studies", "title": "Ablation Studies", "category": "Research And Scientific AI", "focus": "ablation studies", "path": "skills/ablation-studies/SKILL.md"} +{"name": "dataset-documentation", "title": "Dataset Documentation", "category": "Research And Scientific AI", "focus": "dataset documentation", "path": "skills/dataset-documentation/SKILL.md"} +{"name": "statistical-significance-testing", "title": "Statistical Significance Testing", "category": "Research And Scientific AI", "focus": "statistical significance testing", "path": "skills/statistical-significance-testing/SKILL.md"} +{"name": "experiment-design", "title": "Experiment Design", "category": "Research And Scientific AI", "focus": "experiment design", "path": "skills/experiment-design/SKILL.md"} +{"name": "literature-review-automation", "title": "Literature Review Automation", "category": "Research And Scientific AI", "focus": "literature review automation", "path": "skills/literature-review-automation/SKILL.md"} +{"name": "bioinformatics-ml", "title": "Bioinformatics ML", "category": "Research And Scientific AI", "focus": "bioinformatics ML", "path": "skills/bioinformatics-ml/SKILL.md"} +{"name": "chemistry-ml", "title": "Chemistry ML", "category": "Research And Scientific AI", "focus": "chemistry ML", "path": "skills/chemistry-ml/SKILL.md"} +{"name": "materials-discovery-ml", "title": "Materials Discovery ML", "category": "Research And Scientific AI", "focus": "materials discovery ML", "path": "skills/materials-discovery-ml/SKILL.md"} +{"name": "climate-modeling-ml", "title": "Climate Modeling ML", "category": "Research And Scientific AI", "focus": "climate modeling ML", "path": "skills/climate-modeling-ml/SKILL.md"} +{"name": "physics-informed-neural-networks", "title": "Physics Informed Neural Networks", "category": "Research And Scientific AI", "focus": "physics informed neural networks", "path": "skills/physics-informed-neural-networks/SKILL.md"} +{"name": "simulation-surrogate-models", "title": "Simulation Surrogate Models", "category": "Research And Scientific AI", "focus": "simulation surrogate models", "path": "skills/simulation-surrogate-models/SKILL.md"} +{"name": "geospatial-ml", "title": "Geospatial ML", "category": "Research And Scientific AI", "focus": "geospatial ML", "path": "skills/geospatial-ml/SKILL.md"} +{"name": "scientific-visualization", "title": "Scientific Visualization", "category": "Research And Scientific AI", "focus": "scientific visualization", "path": "skills/scientific-visualization/SKILL.md"} +{"name": "research-code-packaging", "title": "Research Code Packaging", "category": "Research And Scientific AI", "focus": "research code packaging", "path": "skills/research-code-packaging/SKILL.md"} +{"name": "notebook-to-pipeline-conversion", "title": "Notebook To Pipeline Conversion", "category": "Research And Scientific AI", "focus": "notebook to pipeline conversion", "path": "skills/notebook-to-pipeline-conversion/SKILL.md"} +{"name": "open-source-model-release", "title": "Open Source Model Release", "category": "Research And Scientific AI", "focus": "open source model release", "path": "skills/open-source-model-release/SKILL.md"} +{"name": "research-artifact-review", "title": "Research Artifact Review", "category": "Research And Scientific AI", "focus": "research artifact review", "path": "skills/research-artifact-review/SKILL.md"} +{"name": "ethics-review-support", "title": "Ethics Review Support", "category": "Research And Scientific AI", "focus": "ethics review support", "path": "skills/ethics-review-support/SKILL.md"} +{"name": "citation-graph-analysis", "title": "Citation Graph Analysis", "category": "Research And Scientific AI", "focus": "citation graph analysis", "path": "skills/citation-graph-analysis/SKILL.md"} +{"name": "knowledge-graph-construction", "title": "Knowledge Graph Construction", "category": "Research And Scientific AI", "focus": "knowledge graph construction", "path": "skills/knowledge-graph-construction/SKILL.md"} +{"name": "synthetic-control-studies", "title": "Synthetic Control Studies", "category": "Research And Scientific AI", "focus": "synthetic control studies", "path": "skills/synthetic-control-studies/SKILL.md"} +{"name": "reproducibility-audits", "title": "Reproducibility Audits", "category": "Research And Scientific AI", "focus": "reproducibility audits", "path": "skills/reproducibility-audits/SKILL.md"} +{"name": "grant-proposal-technical-review", "title": "Grant Proposal Technical Review", "category": "Research And Scientific AI", "focus": "grant proposal technical review", "path": "skills/grant-proposal-technical-review/SKILL.md"}