Skill audit report
Library for Semi-Automated Data Science
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO62
347 GitHub stars
Stars/forks activity
INFO62
347 stars, 83 forks; issue activity unavailable in current metadata
Recent maintenance
INFO76
4mo since push
License clarity
PASS86
Apache-2.0
README/SKILL.md completeness
INFO74
Public metadata needs stronger README/SKILL.md context
Dependency/runtime risk
PASS90
no major dependency risk hints in public metadata
Install availability
PASS92
npx skills add IBM/lale
Install command safety
PASS92
standard package or runtime install path
Permission surface
PASS86
filesystem or document access
Repository evidence
PASS86
https://github.com/IBM/lale
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add IBM/lale
Repository
88
https://github.com/IBM/lale
License
86
Apache-2.0
Maintenance
76
4mo since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
84
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
347 stars, 83 forks; issue activity unavailable in current metadata
Adoption
68
347 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.
Compare nearby options
Cross-platform, customizable ML solutions for live and streaming media.
36K Stars · Audit report
An Open Source Machine Learning Framework for Everyone
196K Stars · Audit report
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
162K Stars · Audit report