Skill audit report
企业数字分身建库工具。从企业名称 + 本地资料 + 公开信息出发，一次性构建一个完整的、标准化的企业分身仓库（AGENTS.md + 企业画像 + 内容资产 + 文风样本 + 调研记录），该仓库可直接被 enterprise-clone-writer 消费进行内容写作。 **强触发场景**： - 「给这家企业建一个数字分身」「构建企业分身仓库」 - 「把这家企业的资料整理成 AI 能用的分身」 - 交付团队需要标准化地给客户企业建分身 **不要用在**： - 分身仓库已建好后的写作任务（用 enterprise-clone-writer） - 个人创作者写作分身（用 writing-clone-profile） - 只是整理企业资料但不建分身仓库
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO76
576 GitHub stars
Stars/forks activity
INFO71
576 stars, 61 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
3d since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS86
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 zjp1997720/zhijian-skills --skill enterprise-clone-builder
Install command safety
PASS92
standard package or runtime install path
Permission surface
PASS86
filesystem or document access
Repository evidence
PASS86
https://github.com/zjp1997720/zhijian-skills/tree/main/skills/enterprise-clone-builder
Review status
INFO66
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add zjp1997720/zhijian-skills --skill enterprise-clone-builder
Repository
88
https://github.com/zjp1997720/zhijian-skills/tree/main/skills/enterprise-clone-builder
License
86
MIT
Maintenance
100
3d since push
AI review
55
SKILL.md references several reference files (e.g., web-clipper-usage.md) that are not fully included in the provided excerpt, but they are expected to exist in the repository.
README/SKILL.md completeness
86
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
576 stars, 61 forks; issue activity unavailable in current metadata
Adoption
88
576 GitHub stars
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.
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