Skill audit report
Structure reproducible Jupyter notebooks with a fixed section layout, hoisted configuration, and leakage-free scikit-learn pipelines. Use when exploring a dataset, training a first model, or preparing a notebook for promotion.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
FAIL30
22 GitHub stars
Stars/forks activity
FAIL32
22 stars, 4 forks; issue activity unavailable in current metadata
Recent maintenance
PASS88
1mo since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
PASS82
database surface
Install availability
PASS92
npx skills add MLOps-Courses/mlops-coding-skills --skill mlops-prototyping
Install command safety
PASS92
standard package or runtime install path
Permission surface
INFO74
filesystem or document access, database access
Repository evidence
PASS86
https://github.com/MLOps-Courses/mlops-coding-skills/tree/main/mlops-prototyping
Review status
WARN46
AI review approval is missing
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add MLOps-Courses/mlops-coding-skills --skill mlops-prototyping
Repository
88
https://github.com/MLOps-Courses/mlops-coding-skills/tree/main/mlops-prototyping
License
86
MIT
Maintenance
88
1mo since push
AI review
55
Review approval is missing
README/SKILL.md completeness
86
Usable description available
Dependency risk
82
database surface
Install command safety
92
standard package or runtime install path
Permission surface
74
filesystem or document access, database access
Stars/forks activity
32
22 stars, 4 forks; issue activity unavailable in current metadata
Adoption
42
22 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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