Skill audit report
ICCV2019 LearningToPaint audit report.
ICCV2019 - Learning to Paint With Model-based Deep Reinforcement Learning
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
2.3K GitHub stars
Recent maintenance
FAIL38
1y since push
License clarity
PASS86
MIT
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 hzwer/ICCV2019-LearningToPaint
Repository evidence
PASS86
https://github.com/hzwer/ICCV2019-LearningToPaint
Review status
PASS88
AI review data available
Checks
Install and adoption review
Install path
92
npx skills add hzwer/ICCV2019-LearningToPaint
Repository
88
https://github.com/hzwer/ICCV2019-LearningToPaint
License
86
MIT
Maintenance
38
1y 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
2.3K GitHub stars
Warnings
- Repository appears stale
- Repository looks stale
- Quality score needs review
- Recent maintenance: 1y 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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