kishormorol/llm-skills-registry

LLM Skills Registry

226 first-party skills and capabilities across 13 AI assistant ecosystems, each with a category, a description, a usage example, and a link to the vendor's own documentation.

This is the data behind SkillsAllYouNeed.

What counts as a skill here

A skill is a capability the vendor itself ships: something the assistant can do, triggered in a documented way. Third-party plugins and community prompt packs are out of scope, which is what keeps every row checkable against a first-party source.

Covered ecosystems include Claude, Claude Code, ChatGPT, Codex, OpenCode, Cursor, Gemini, Perplexity, Microsoft 365 Copilot, GitHub Copilot, Antigravity, Kiro, and Pi.

Schema

Field	Description
id	Stable identifier, e.g. cl-artifacts
name	Skill name as the vendor calls it
ecosystem	Which assistant ships it
category	Functional grouping, e.g. Visual, Research, Code
status	Stable, beta, or deprecated, as documented
description	What the skill does
trigger / example / howto	How it is invoked in practice
source	Link to first-party documentation

from datasets import load_dataset

skills = load_dataset("kishormorol/llm-skills-registry", split="train")
claude = skills.filter(lambda r: r["ecosystem"] == "Claude")

Uses

Useful for comparing capability coverage across assistants, for grounding "can model X do Y" questions in documentation rather than guesswork, and as a seed list when building agent tooling.

Limitations

Vendor capabilities change quickly, and a registry is a snapshot. Each row carries its source link so you can re-check it. Corrections go through the GitHub repo, which is the source of truth.

Citation

@software{morol_skills_registry,
  author  = {Morol, Md Kishor},
  title   = {SkillsAllYouNeed: An Open Registry of First-Party AI Skills},
  url     = {https://github.com/kishormorol/SkillsAllYouNeed},
  license = {CC-BY-4.0}
}