eval-code-quality
eval-code-quality is an LLM evaluation & observability skill for AI agents, published by Ibrahim-3d in the conductor-orchestrator-superpowers repository on GitHub. Skillspace rates eval-code-quality D (64/100) and it passed the safety scan; the rating is based on static analysis only.
Specialized code quality evaluator for the Evaluate-Loop. Use this for evaluating code implementation tracks where the deliverable is functional code — features, API routes, state management, utilities. Checks build integrity, type safety, code patterns, error handling, dead code, imports, test coverage, and naming conventions. Dispatched by loop-execution-evaluator when track type is 'feature', 'refactor', or 'infrastructure'. Triggered by: 'evaluate code', 'code review', 'quality check', 'build check'.
- Grade
- D
- Quality
- 64 / 100
- Safety
- Passed
- GitHub stars
- 376
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
- 93 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 0 collections
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
Also published in 1 other repo
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