No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by Linked-API · Codex Skill · ★ 77
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is linkedin-skills safe to install? View the security audit →
linkedin-skills A collection of LinkedIn skills for AI agents (Claude Code, Codex, Cursor, Windsurf), powered by LinkedIn CLI () and Linked API. Install One command — detects your installed agents, asks what to install and where, and sets up the prerequisites for you: Or just hand this to your AI agent: Non-interactive (agents / CI) Other commands: , , , (all support ). See . Available skills Prerequisites The installer checks these for you and offers to set them up: Node.js ≥ 20 (npm install -g @li
| Stars | 77 |
| Forks | 14 |
| Language | JavaScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 72.8776478815256/100 |
| Last Updated | 2026-09-29 |
| Created | 2026-02-24 |
| Platforms | node |
| Est. Tokens | ~13k |
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linkedin-skills is LinkedIn automation skills for AI agents – sales, social selling, data extraction, and more.. It is categorized as a Codex Skill with 77 GitHub stars.
linkedin-skills is primarily written in JavaScript. It covers topics such as agent-skills, ai-agents, linkedin.
You can find installation instructions and usage details in the linkedin-skills GitHub repository at github.com/Linked-API/linkedin-skills. The project has 77 stars and 14 forks, indicating an active community.
linkedin-skills is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to linkedin-skills on Agent Skills Hub include cc-skills, excalidraw-skill, semanticscholar-skill. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: