golden-dataset-curation
Use when creating or improving golden datasets for AI evaluation. Defines quality criteria, curation workflows, and multi-agent analysis patterns for test data.
npx skills add majiayu000/claude-skill-registry --skill golden-dataset-curation --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Golden Dataset Curation **Curate high-quality documents for the golden dataset with multi-agent validation** ## Overview This skill provides patterns and workflows for **adding new documents** to the golden dataset with thorough quality analysis. It complements `golden-dataset-management` which handles backup/restore. **When to use this skill:** - Adding new documents to the golden dataset - Classifying content types and difficulty levels - Generating test queries for new documents - Running multi-agent quality analysis --- ## Content Types | Type | Description | Quality Focus | |------|-------------|---------------| | `article` | Technical articles, blog posts | Depth, accuracy, actionability | | `tutorial` | Step-by-step guides | Completeness, clarity, code quality | | `research_paper` | Academic papers, whitepapers | Rigor, citations, methodology | | `documentation` | API docs, reference materials | Accuracy, completeness, examples | | `video_transcript` | Transcribed video content | Structure, coherence, key points | | `code_repository` | README, code analysis | Code quality, documentation | --- ## Difficulty Levels | Level | Semantic Complexity | Expected Score | Characteris
- Overview
- Content Types
- Difficulty Levels
- Quality Dimensions
- Multi-Agent Pipeline
- Decision Thresholds
- Quality Thresholds
- Coverage Balance Guidelines
- Duplicate Prevention Checklist
- Provenance Tracking
- Langfuse Integration
- Trace Structure
- Managed Prompts
- References
What does the golden-dataset-curation skill do?
Use when creating or improving golden datasets for AI evaluation. Defines quality criteria, curation workflows, and multi-agent analysis patterns for test data.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill golden-dataset-curation --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.