Skill audit report
Practical Machine Learning With Python audit report.
Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
OpenAgentSkill Trust Score
Stars, maintenance, license, docs, dependency risk, 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
PASS86
2.4K GitHub stars
Recent maintenance
FAIL22
2y since push
License clarity
PASS86
Apache-2.0
README/SKILL.md completeness
PASS90
Metadata includes enough usage and workflow context
Dependency risk
PASS90
no major dependency risk hints in public metadata
Install availability
PASS92
npx skills add dipanjanS/practical-machine-learning-with-python
Repository evidence
PASS86
https://github.com/dipanjanS/practical-machine-learning-with-python
Review status
PASS88
AI review data available
Checks
Install and adoption review
Install path
92
npx skills add dipanjanS/practical-machine-learning-with-python
Repository
88
https://github.com/dipanjanS/practical-machine-learning-with-python
License
86
Apache-2.0
Maintenance
20
2y 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
Adoption
88
2.4K GitHub stars
Warnings
- Repository appears stale
- Repository looks stale
- Quality score needs review
- Recent maintenance: 2y 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.
Compare nearby options