Skill audit report
Llm Applications audit report.
A comprehensive guide to building RAG-based LLM applications for production.
OpenAgentSkill Trust Score
Stars, maintenance, license, docs, dependency risk, and installability.
The Trust Score is OpenAgentSkill's adoption layer. It is designed to help an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
PASS86
1.9K GitHub stars
Recent maintenance
FAIL38
2y since push
License clarity
PASS86
CC-BY-4.0
README/SKILL.md completeness
INFO74
Public metadata needs stronger README/SKILL.md context
Dependency risk
PASS90
no major dependency risk hints in public metadata
Install availability
PASS92
npx skills add ray-project/llm-applications
Repository evidence
PASS86
https://github.com/ray-project/llm-applications
Review status
PASS88
AI review data available
Checks
Install and adoption review
Install path
92
npx skills add ray-project/llm-applications
Repository
88
https://github.com/ray-project/llm-applications
License
86
CC-BY-4.0
Maintenance
38
2y since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
84
Usable description available
Dependency risk
90
no major dependency risk hints in public metadata
Adoption
88
1.9K GitHub stars
Warnings
- Repository appears stale
- Repository looks stale
- Quality score needs review
- Recent maintenance: 2y since push
Method
This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.
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