llm-golden-dataset-builder
llm-golden-dataset-builder is an LLM evaluation & observability skill for AI agents, published by latitude-dev in the eval-skills repository on GitHub. Skillspace rates llm-golden-dataset-builder C (72/100) and it passed the safety scan; the rating is based on static analysis only.
Use this skill when a developer wants to build or expand a golden dataset for regression testing. Triggers on: "build a golden dataset", "create a test dataset", "curate eval examples", "promote logs to dataset", "build regression test cases", "I need a golden dataset", "select good examples for testing", "create a baseline dataset", "curate passing traces". Takes production logs with eval results and helps the developer select, review, and curate representative examples into a structured golden dataset ready for regression testing.
- Grade
- C
- Quality
- 72 / 100
- Safety
- Passed
- GitHub stars
- 20
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 84 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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