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README.md

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+---
+dataset_info:
+  features:
+  - name: messages
+    list:
+    - name: content
+      dtype: string
+    - name: role
+      dtype: string
+  splits:
+  - name: train
+    num_bytes: 3021564
+    num_examples: 3043
+  download_size: 1331200
+  dataset_size: 3021564
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+---
+
+# TradeGuru Electrical Fault-Finding SFT Dataset
+
+Synthetic training data for fine-tuning **Google Gemma 3 27B** as a specialised electrical fault-finding assistant for the **TradeGuru** iOS app.
+
+## Dataset Details
+
+- **Examples**: 3,043 conversation pairs
+- **Format**: Gemma SFT (`messages` column with `user`/`model` roles)
+- **Model responses**: Structured JSON matching the TradeGuru iOS app `ContentBlock` schema
+
+## Source Knowledge
+
+- 127-page professional electrical fault-finding guide covering domestic, commercial, and industrial domains
+- 522 practical training summaries across 18 categories (testing, wiring, tools, earthing, safety, and more)
+
+## Categories Covered (26)
+
+Electrical basics, safety/PPE, LOTO, fault-finding process, testing equipment, CAT ratings, domestic (RCD faults, no power, breaker tripping, hot water), commercial (HVAC, emergency lighting, power distribution), industrial (motors, PLCs, sensors), wiring (switches, power points), earthing, cable work, tools, apprentice skills, 3-phase, roof work, switchboards.
+
+## Response Format
+
+Model responses are valid JSON objects with a `blocks` array containing typed content blocks:
+
+```json
+{"blocks": [
+  {"type": "text", "content": "..."},
+  {"type": "step_list", "title": "...", "steps": ["...", "..."]},
+  {"type": "warning", "content": "..."},
+  {"type": "callout", "content": "...", "style": "tip"}
+]}
+```
+
+**Block types**: text, heading, step_list, warning, code, parts_list, regulation, callout, table, link
+
+## Generation
+
+- Generated via GoodWork swarm (Z.AI / NullClaw) with parallel agent orchestration
+- Post-processed with validation pipeline: JSON schema checks, deduplication, compliance filtering
+- Quality-filtered from 15,032 raw pairs down to 3,043 unique validated examples
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("THEARTISTISME/tradeguru-electrical-sft")
+```