Skill audit report
agentUniverse is a LLM multi-agent framework that allows developers to easily build multi-agent applications.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
PASS86
2.3K GitHub stars
Stars/forks activity
PASS83
2.3K stars, 418 forks; issue activity unavailable in current metadata
Recent maintenance
PASS88
2mo since push
License clarity
PASS86
Apache-2.0
README/SKILL.md completeness
PASS90
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 agentuniverse-ai/agentUniverse
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/agentuniverse-ai/agentUniverse
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add agentuniverse-ai/agentUniverse
Repository
88
https://github.com/agentuniverse-ai/agentUniverse
License
86
Apache-2.0
Maintenance
88
2mo 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
Install command safety
92
standard package or runtime install path
Permission surface
100
no high-risk permission surface in public metadata
Stars/forks activity
83
2.3K stars, 418 forks; issue activity unavailable in current metadata
Adoption
88
2.3K GitHub stars
Warnings
No major warnings from available metadata.
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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