Skill audit report

Awesome Autoresearch audit report.

Curated list of AutoResearch use cases with optimization traces and open source implementations

REVIEWED · REVIEWSafe to tryGenerated Jun 16, 2026Heuristic metadata audit
92
Audit
89
Trust
87
Quality
97
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

INFO

76

980 GitHub stars

Recent maintenance

PASS

100

13d since push

License clarity

PASS

86

CC0-1.0

README/SKILL.md completeness

PASS

90

Metadata includes enough usage and workflow context

Dependency risk

PASS

90

no major dependency risk hints in public metadata

Install availability

PASS

92

npx skills add WecoAI/awesome-autoresearch

Repository evidence

PASS

86

https://github.com/WecoAI/awesome-autoresearch

Review status

PASS

88

AI review data available

Checks

Install and adoption review

8 passed · 1 review

Install path

92

PASS

npx skills add WecoAI/awesome-autoresearch

Repository

88

PASS

https://github.com/WecoAI/awesome-autoresearch

License

86

PASS

CC0-1.0

Maintenance

100

PASS

13d since push

AI review

88

PASS

Approved with no listed issues

README/SKILL.md completeness

90

PASS

Usable description available

Dependency risk

90

PASS

no major dependency risk hints in public metadata

Adoption

88

PASS

980 GitHub stars

Warnings

  • Quality score needs review

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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