Skill audit report

AgentsMesh audit report.

The AI Agent Workforce Platform — where teams scale beyond headcount. Give every team member an AI agent squad.

REVIEWED · REVIEWSafe to tryGenerated Jun 16, 2026Heuristic metadata audit
93
Audit
89
Trust
100
Quality
86
Security
100
Maintain
92
Install

OpenAgentSkill Trust Score

89
Production candidate

Stars, maintenance, license, docs, dependency risk, 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

PASS

86

2.2K GitHub stars

Recent maintenance

PASS

100

1d since push

License clarity

WARN

42

Unknown

README/SKILL.md completeness

PASS

90

Metadata includes enough usage and workflow context

Dependency risk

INFO

72

command execution surface

Install availability

PASS

92

npx skills add AgentsMesh/AgentsMesh

Repository evidence

PASS

86

https://github.com/AgentsMesh/AgentsMesh

Review status

PASS

88

AI review data available

Checks

Install and adoption review

6 passed · 4 review

Install path

92

PASS

npx skills add AgentsMesh/AgentsMesh

Repository

88

PASS

https://github.com/AgentsMesh/AgentsMesh

License

45

CHECK

Unknown

Maintenance

100

PASS

1d since push

AI review

88

PASS

Approved with no listed issues

README/SKILL.md completeness

90

PASS

Usable description available

Dependency risk

72

CHECK

command execution surface

Adoption

88

PASS

2.2K GitHub stars

Warnings

  • License is unclear
  • 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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