Skill audit report

AIGC Interview Book audit report.

【三年面试五年模拟】AIGC/LLM/AI Agent算法工程师面试秘籍。涵盖AIGC、LLM大模型、AI Agent、传统深度学习、自动驾驶、机器学习、计算机视觉、自然语言处理、强化学习、大数据挖掘、具身智能、元宇宙、AGI等AI行业面试笔试干货经验与核心知识。

VERIFIED · ALLOWSafe to tryGenerated Jun 16, 2026Heuristic metadata audit
97
Audit
96
Trust
100
Quality
97
Security
100
Maintain
92
Install

OpenAgentSkill Trust Score

96
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

3.9K GitHub stars

Recent maintenance

PASS

100

Pushed today

License clarity

PASS

86

GPL-3.0

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 WeThinkIn/AIGC-Interview-Book

Repository evidence

PASS

86

https://github.com/WeThinkIn/AIGC-Interview-Book

Review status

PASS

88

AI review data available

Checks

Install and adoption review

8 passed · 0 review

Install path

92

PASS

npx skills add WeThinkIn/AIGC-Interview-Book

Repository

88

PASS

https://github.com/WeThinkIn/AIGC-Interview-Book

License

86

PASS

GPL-3.0

Maintenance

100

PASS

Pushed today

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

3.9K GitHub stars

Warnings

No major warnings detected 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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