Skill audit report
EVA audit report.
EVA is an AI-assisted penetration testing agent that enhances offensive security workflows by providing structured attack guidance, contextual analysis, and multi-backend AI integration.
OpenAgentSkill Trust Score
Stars, maintenance, license, docs, install safety, permission surface, and installability.
The Trust Score is OpenAgentSkill's adoption layer. It is designed to help an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO62
403 GitHub stars
Stars/forks activity
INFO62
403 stars, 76 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
1d since push
License clarity
WARN42
Unknown
README/SKILL.md completeness
PASS90
Metadata includes enough usage and workflow context
Dependency/runtime risk
INFO72
command execution surface
Install availability
PASS92
npx skills add ARCANGEL0/EVA
Install command safety
PASS92
standard package or runtime install path
Permission surface
INFO62
shell or command execution, filesystem or document access
Repository evidence
PASS86
https://github.com/ARCANGEL0/EVA
Review status
PASS88
AI review data available
Checks
Install and adoption review
Install path
92
npx skills add ARCANGEL0/EVA
Repository
88
https://github.com/ARCANGEL0/EVA
License
45
Unknown
Maintenance
100
1d since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
90
Usable description available
Dependency risk
72
command execution surface
Install command safety
92
standard package or runtime install path
Permission surface
62
shell or command execution, filesystem or document access
Stars/forks activity
62
403 stars, 76 forks; issue activity unavailable in current metadata
Adoption
68
403 GitHub stars
Warnings
- License is unclear
- Quality score needs review
- License clarity: Unknown
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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