Skill audit report
Customer/user segmentation with actionable insights. Use when identifying distinct customer groups, analyzing segment-specific behavior, profiling high-value segments, or testing segmentation hypotheses.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO62
446 GitHub stars
Stars/forks activity
INFO62
446 stars, 80 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
1d since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS86
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 nimrodfisher/data-analytics-skills --skill segmentation-analysis
Install command safety
PASS92
standard package or runtime install path
Permission surface
PASS100
no high-risk permission surface in public metadata
Repository evidence
PASS86
https://github.com/nimrodfisher/data-analytics-skills/tree/main/03-data-analysis-investigation/segmentation-analysis
Review status
INFO66
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add nimrodfisher/data-analytics-skills --skill segmentation-analysis
Repository
88
https://github.com/nimrodfisher/data-analytics-skills/tree/main/03-data-analysis-investigation/segmentation-analysis
License
86
MIT
Maintenance
100
1d since push
AI review
55
The script `segmentation_runner.py` does not perform k-means clustering or generate elbow/silhouette plots as described in SKILL.md; it only profiles pre-defined segments using index scores.
README/SKILL.md completeness
86
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
100
no high-risk permission surface in public metadata
Stars/forks activity
62
446 stars, 80 forks; issue activity unavailable in current metadata
Adoption
68
446 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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