llm-regression-runner
llm-regression-runner is an LLM evaluation & observability skill for AI agents, published by latitude-dev in the eval-skills repository on GitHub. Skillspace rates llm-regression-runner 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 test a prompt change against a golden dataset and see what broke. Triggers on: "run my evals", "test this prompt change", "check for regressions", "did I break anything", "run regression tests", "test against golden dataset", "compare prompt versions", "is it safe to deploy", "run offline evals", "what changed after my prompt update", "eval before deploying". Runs a golden dataset against the current prompt, scores each case with available judges, compares results against a saved baseline, and produces a pass/fail report with a clear deploy recommendation.
- 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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