Skill audit report

lark-note Audit report.

仅当用户或上游配置显式指定 lark-note 时使用,相关请求统一交由 lark-meeting 技能处理。

REVIEWED · REVIEWSafe to tryGenerated Nov 4, 2026Heuristic metadata audit
86
Audit
82
Trust
86
Quality
85
Security
88
Maintain
92
Install

OpenAgentSkill Trust Score

82
Strong shortlist

OpenAgentSkill Trust Score

The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.

GitHub adoption

PASS

100

17K GitHub stars

Stars/forks activity

PASS

97

17K stars, 1.4K forks; issue activity unavailable in current metadata

Recent maintenance

PASS

88

2mo since push

License clarity

PASS

86

MIT

README/SKILL.md completeness

INFO

70

Public metadata needs stronger README/SKILL.md context

Dependency/runtime risk

INFO

72

command execution surface

Install availability

PASS

92

npx skills add larksuite/cli --skill lark-note

Install command safety

PASS

92

standard package or runtime install path

Permission surface

INFO

76

shell or command execution

Repository evidence

PASS

86

https://github.com/larksuite/cli/tree/main/skills/lark-note

Review status

PASS

88

AI review data available

Agent Proven outcomes

INFO

54

No agent outcome data yet

Checks

Install and adoption review

9 Passed · 3 Needs review

Install path

92

PASS

npx skills add larksuite/cli --skill lark-note

Repository

88

PASS

https://github.com/larksuite/cli/tree/main/skills/lark-note

License

86

PASS

MIT

Maintenance

88

PASS

2mo since push

AI review

88

PASS

Approved with no listed issues

README/SKILL.md completeness

84

PASS

Usable description available

Dependency risk

72

CHECK

command execution surface

Install command safety

92

PASS

standard package or runtime install path

Permission surface

76

CHECK

shell or command execution

Stars/forks activity

97

PASS

17K stars, 1.4K forks; issue activity unavailable in current metadata

Adoption

88

PASS

17K 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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