Skill audit report
VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO76
588 GitHub stars
Stars/forks activity
INFO71
588 stars, 112 forks; issue activity unavailable in current metadata
Recent maintenance
INFO76
4mo since push
License clarity
PASS86
GPL-3.0
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 proroklab/VectorizedMultiAgentSimulator
Install command safety
PASS92
standard package or runtime install path
Permission surface
PASS86
filesystem or document access
Repository evidence
PASS86
https://github.com/proroklab/VectorizedMultiAgentSimulator
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add proroklab/VectorizedMultiAgentSimulator
Repository
88
https://github.com/proroklab/VectorizedMultiAgentSimulator
License
86
GPL-3.0
Maintenance
76
4mo 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
86
filesystem or document access
Stars/forks activity
71
588 stars, 112 forks; issue activity unavailable in current metadata
Adoption
88
588 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
The API to search, scrape, and interact with the web at scale. 🔥
139K Stars · Audit report
Daytona is a Secure and Elastic Infrastructure for Running AI-Generated Code
72K Stars · Audit report
AI generates a real, editable PowerPoint from any document — native shapes & animations, speaker notes voiced as audio narration, and the option to follow your own .pptx template, not slide images · by Hugo He
37K Stars · Audit report