Skill audit report
Systematic data quality validation before modeling. Use when checking for gaps, outliers, stale prices, or schema violations in datasets.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
FAIL30
20 GitHub stars
Stars/forks activity
FAIL37
20 stars, 11 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
6d since push
License clarity
PASS86
Apache-2.0
README/SKILL.md completeness
INFO76
Public metadata needs stronger README/SKILL.md context
Dependency/runtime risk
PASS82
network or browser surface
Install availability
PASS92
npx skills add ml4t/skills --skill ml4t-validate-data
Install command safety
PASS92
standard package or runtime install path
Permission surface
INFO74
network or browser access, database access
Repository evidence
PASS86
https://github.com/ml4t/skills/tree/main/data/validate-data
Review status
WARN46
AI review approval is missing
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add ml4t/skills --skill ml4t-validate-data
Repository
88
https://github.com/ml4t/skills/tree/main/data/validate-data
License
86
Apache-2.0
Maintenance
100
6d since push
AI review
55
Review approval is missing
README/SKILL.md completeness
84
Usable description available
Dependency risk
82
network or browser surface
Install command safety
92
standard package or runtime install path
Permission surface
74
network or browser access, database access
Stars/forks activity
37
20 stars, 11 forks; issue activity unavailable in current metadata
Adoption
42
20 GitHub stars
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
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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