Skill audit report
Awesome Machine Learning On Source Code audit report.
Cool links & research papers related to Machine Learning applied to source code (MLonCode)
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
PASS94
6.6K GitHub stars
Recent maintenance
FAIL22
6y since push
License clarity
PASS86
CC-BY-SA-4.0
README/SKILL.md completeness
PASS90
Metadata includes enough usage and workflow context
Dependency risk
PASS90
no major dependency risk hints in public metadata
Install availability
PASS92
npx skills add src-d/awesome-machine-learning-on-source-code
Repository evidence
PASS86
https://github.com/src-d/awesome-machine-learning-on-source-code
Review status
PASS88
AI review data available
Checks
Install and adoption review
Install path
92
npx skills add src-d/awesome-machine-learning-on-source-code
Repository
88
https://github.com/src-d/awesome-machine-learning-on-source-code
License
86
CC-BY-SA-4.0
Maintenance
20
6y since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
90
Usable description available
Dependency risk
90
no major dependency risk hints in public metadata
Adoption
88
6.6K GitHub stars
Warnings
- Repository appears stale
- Repository looks stale
- Quality score needs review
- Recent maintenance: 6y 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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