Skill audit report
当用户纠结要不要学某个东西、学到什么程度，或在做时间/精力/项目取舍时使用。用「简易策略」先逼问要解决的既定问题，检验现有知识能否搞定，评估知识贬值速度与 ROI，用「探索 vs 应用」判断该学新的还是用现有的，给出「学 / 不学 / 只学最小够用」的结论，避免囤积会贬值的知识。触发场景：要不要学 X、值不值得深入、学到什么程度够、时间不够该学啥、该深挖还是够用就行。
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO62
263 GitHub stars
Stars/forks activity
WARN57
263 stars, 41 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
5d since push
License clarity
PASS86
MIT
README/SKILL.md completeness
INFO76
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 Li-Evan/Bloom --skill learn-occam
Install command safety
PASS92
standard package or runtime install path
Permission surface
PASS100
no high-risk permission surface in public metadata
Repository evidence
PASS86
https://github.com/Li-Evan/Bloom/tree/main/skills/learn-occam
Review status
WARN46
AI review approval is missing
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add Li-Evan/Bloom --skill learn-occam
Repository
88
https://github.com/Li-Evan/Bloom/tree/main/skills/learn-occam
License
86
MIT
Maintenance
100
5d since push
AI review
55
Review approval is missing
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
100
no high-risk permission surface in public metadata
Stars/forks activity
57
263 stars, 41 forks; issue activity unavailable in current metadata
Adoption
68
263 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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