Skill audit report
Dance audit report.
DANCE: a deep learning library and benchmark platform for single-cell analysis
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
INFO62
389 GitHub stars
Stars/forks activity
WARN57
389 stars, 37 forks; issue activity unavailable in current metadata
Recent maintenance
PASS88
2mo since push
License clarity
PASS86
BSD-2-Clause
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 OmicsML/dance
Install command safety
PASS92
standard package or runtime install path
Permission surface
PASS86
filesystem or document access
Repository evidence
PASS86
https://github.com/OmicsML/dance
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 OmicsML/dance
Repository
88
https://github.com/OmicsML/dance
License
86
BSD-2-Clause
Maintenance
88
2mo 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
57
389 stars, 37 forks; issue activity unavailable in current metadata
Adoption
68
389 GitHub stars
Warnings
- Quality score needs review
- Stars/forks activity: 389 stars, 37 forks; issue activity unavailable in current metadata
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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