Assess
7,000+ AI-evaluated skills with quality ratings — a large catalog if you trust the scoring.
Why It Matters
skillhub.club offers a broad catalog of skills for Claude, Codex, Gemini, and OpenCode with community-driven quality ratings. The twist: quality scores are AI-evaluated. That's efficient for scale but introduces a "who watches the watchers" problem — the ratings are only as good as the evaluation methodology behind them.
Strengths
- Large catalog (7,000+ skills) spanning multiple agent platforms
- Quality rating system helps surface better skills from the noise
- Community-driven contributions keep the catalog growing
Limitations
- AI-evaluated quality scores lack transparency — methodology is a black box
- No security scanning mentioned; quality ratings are not security audits
- Assess rating: promising scale, but evaluate the evaluation before relying on it
Risks
- AI evaluating AI-generated skills is circular reasoning — LLMs rating LLM instructions have well-documented blind spots
- Quality scores without transparent methodology can mislead developers into trusting dangerous skills
- 7,000+ skills sounds large but many are scraped duplicates with minor variations
- No organizational backing or funding model visible — longevity is a real question