Skill audit report
LinkedIn automation skills for AI agents – sales, social selling, data extraction, and more.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
WARN48
42 GitHub stars
Stars/forks activity
WARN43
42 stars, 7 forks; issue activity unavailable in current metadata
Recent maintenance
PASS88
2mo since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS100
Metadata includes enough usage and workflow context
Dependency/runtime risk
WARN46
command execution surface, credential or environment access
Install availability
PASS92
npx skills add Linked-API/linkedin-skills
Install command safety
PASS92
standard package or runtime install path
Permission surface
FAIL36
secrets or environment access, shell or command execution
Repository evidence
PASS86
https://github.com/Linked-API/linkedin-skills
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add Linked-API/linkedin-skills
Repository
88
https://github.com/Linked-API/linkedin-skills
License
86
MIT
Maintenance
88
2mo since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
100
Usable description available
Dependency risk
46
command execution surface, credential or environment access
Install command safety
92
standard package or runtime install path
Permission surface
36
secrets or environment access, shell or command execution
Stars/forks activity
43
42 stars, 7 forks; issue activity unavailable in current metadata
Adoption
42
42 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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