Skill audit report
Interactive data profiling and cleaning assistant for medical research. Three-stage workflow (profile, flag, code-generate) with user approval gates at each step. Handles missing values, outliers, duplicates, and type mismatches in CSV/Excel clinical data. Does NOT auto-clean — all decisions require researcher confirmation.
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO62
288 GitHub stars
Stars/forks activity
INFO62
288 stars, 69 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
1d since push
License clarity
PASS86
MIT
README/SKILL.md completeness
INFO76
Public metadata needs stronger README/SKILL.md context
Dependency/runtime risk
INFO64
command execution surface, network or browser surface
Install availability
PASS92
npx skills add Aperivue/medsci-skills --skill clean-data
Install command safety
PASS92
standard package or runtime install path
Permission surface
WARN48
shell or command execution, filesystem or document access
Repository evidence
PASS86
https://github.com/Aperivue/medsci-skills/tree/main/skills/clean-data
Review status
INFO66
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add Aperivue/medsci-skills --skill clean-data
Repository
88
https://github.com/Aperivue/medsci-skills/tree/main/skills/clean-data
License
86
MIT
Maintenance
100
1d since push
AI review
55
The SKILL.md references a `/deidentify` skill that may not be available in the same repository; ensure it is present or provide a fallback for PHI handling.
README/SKILL.md completeness
84
Usable description available
Dependency risk
64
command execution surface, network or browser surface
Install command safety
92
standard package or runtime install path
Permission surface
48
shell or command execution, filesystem or document access
Stars/forks activity
62
288 stars, 69 forks; issue activity unavailable in current metadata
Adoption
68
288 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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