llm-evals-audit

llm-evals-audit is an LLM evaluation & observability skill for AI agents, published by latitude-dev in the eval-skills repository on GitHub. Skillspace rates llm-evals-audit 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 check whether their existing evaluations are trustworthy and well-targeted. Triggers on: "audit my evals", "are my evals any good", "review my evaluation setup", "check my LLM judges", "are my evaluations reliable", "something feels off with my eval scores", "inherited an eval system", "my evals are passing but the product feels broken", "post-build eval check", "validate my eval pipeline". Inspects existing eval artifacts — judge prompts, annotation data, issue reports, alignment scores — and produces a prioritized findings report with a concrete fix for each problem. Do NOT use this to build new evals from scratch — use llm-evals-checklist first, then llm-judge-creator.

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.

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