Skill audit report
Seaborn Tutorial audit report.
This repository is my attempt to help Data Science aspirants gain necessary Data Visualization skills required to progress in their career. It includes all the types of plot offered by Seaborn, applied on random datasets.
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
198 GitHub stars
Stars/forks activity
INFO62
198 stars, 97 forks; issue activity unavailable in current metadata
Recent maintenance
FAIL22
6y since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS90
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 clair513/Seaborn-Tutorial
Install command safety
PASS92
standard package or runtime install path
Permission surface
PASS86
filesystem or document access
Repository evidence
PASS86
https://github.com/clair513/Seaborn-Tutorial
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 clair513/Seaborn-Tutorial
Repository
88
https://github.com/clair513/Seaborn-Tutorial
License
86
MIT
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
Install command safety
92
standard package or runtime install path
Permission surface
86
filesystem or document access
Stars/forks activity
62
198 stars, 97 forks; issue activity unavailable in current metadata
Adoption
68
198 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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