eval-agents

eval-agents is an LLM evaluation & observability skill for AI agents, published by me2resh in the apexyard repository on GitHub. Skillspace rates eval-agents D (61/100) and it passed the safety scan; the rating is based on static analysis only.

Score a review agent (Rex/Hakim/Tariq) against a labeled PR corpus — ground-truth defect-set overlap, never a prose rubric. Headline metric is approve-precision.

Grade
D
Quality
61 / 100
Safety
Passed
GitHub stars
479

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.

View source on GitHubme2resh/apexyard

Our review

Architecture
83 / 100
Maturity
Structured: ships references or scripts
Security scan
Low-risk patterns
License
MIT
Adoption
Adopted by 0 other repositories, in 0 collections

What the scanner flagged

  • mentions secrets in text

Not checked yet

  • Category is a classifier prediction; no model has read this skill 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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