Skill audit report
Find implementable ML training recipes from papers, datasets, docs, and code. Use when the user wants to fine-tune, train, reproduce, or choose a practical ML method, dataset, hyperparameter setup, or benchmark recipe.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
PASS94
9.8K GitHub stars
Stars/forks activity
PASS93
9.8K stars, 1.1K forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
9d since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
PASS90
no major dependency risk hints in public metadata
Install availability
PASS92
npx skills add Companion-Inc/feynman --skill ml-training-recipe
Install command safety
PASS92
standard package or runtime install path
Permission surface
INFO76
shell or command execution
Repository evidence
PASS86
https://github.com/Companion-Inc/feynman/tree/main/skills/ml-training-recipe
Review status
WARN46
AI review approval is missing
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add Companion-Inc/feynman --skill ml-training-recipe
Repository
88
https://github.com/Companion-Inc/feynman/tree/main/skills/ml-training-recipe
License
86
MIT
Maintenance
100
9d since push
AI review
55
Review approval is missing
README/SKILL.md completeness
86
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
76
shell or command execution
Stars/forks activity
93
9.8K stars, 1.1K forks; issue activity unavailable in current metadata
Adoption
88
9.8K GitHub stars
Warnings
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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