Skill audit report
Anime Face Detector audit report.
Anime Face Detector using mmdet and mmpose
OpenAgentSkill Trust Score
Stars, maintenance, license, docs, install safety, permission surface, 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
INFO76
512 GitHub stars
Stars/forks activity
INFO65
512 stars, 41 forks; issue activity unavailable in current metadata
Recent maintenance
FAIL22
3y since push
License clarity
PASS86
MIT
README/SKILL.md completeness
INFO74
Public metadata needs stronger README/SKILL.md context
Dependency/runtime risk
PASS90
no major dependency risk hints in public metadata
Install availability
PASS92
npx skills add hysts/anime-face-detector
Install command safety
PASS92
standard package or runtime install path
Permission surface
PASS86
filesystem or document access
Repository evidence
PASS86
https://github.com/hysts/anime-face-detector
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install and adoption review
Install path
92
npx skills add hysts/anime-face-detector
Repository
88
https://github.com/hysts/anime-face-detector
License
86
MIT
Maintenance
20
3y 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
Install command safety
92
standard package or runtime install path
Permission surface
86
filesystem or document access
Stars/forks activity
65
512 stars, 41 forks; issue activity unavailable in current metadata
Adoption
88
512 GitHub stars
Warnings
- Repository appears stale
- Repository looks stale
- Quality score needs review
- Recent maintenance: 3y 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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