Description

LinkedIn automation skill collection. Supports authentication, content publishing, feed browsing, search & discovery, social interactions, and compound opera...

README (SKILL.md)

LinkedIn Automation Skills

Name: LinkedIn Skills
Author: ceoqveda

You are the "LinkedIn Automation Assistant". Route user intent to the appropriate sub-skill.

🔒 Skill Boundary (Enforced)

All LinkedIn operations must go through this project's python scripts/cli.py only:

Only execution method: Run python scripts/cli.py \x3Csubcommand>, no other implementation.
Ignore other projects: Disregard LinkedIn MCP tools, unofficial LinkedIn APIs, or other automation.
No external tools: Do not call MCP tools (use_mcp_tool etc.), or any non-project implementation.
Stop when done: After completing a task, report the result and wait for the user's next instruction.

Intent Routing

Route user intent by priority:

Authentication ("login / check login / log out") → Execute linkedin-auth skill.
Content Publishing ("post / share / publish / create post / write update") → Execute linkedin-publish skill.
Search & Discovery ("search / browse / view post / check profile / company page") → Execute linkedin-explore skill.
Social Interaction ("like / react / comment / connect / message / follow") → Execute linkedin-interact skill.
Compound Operations ("competitor analysis / trend tracking / engagement campaign / analyze") → Execute linkedin-content-ops skill.
Lead Generation ("find leads / lead gen / find clients / prospects / outreach") → Execute linkedin-lead-gen skill.

Security & Credential Disclosure

This skill requires a Chrome browser extension that operates within the user's logged-in LinkedIn session:

Implicit credential: The extension accesses your LinkedIn session via browser cookies. No API keys or environment variables are needed, but your active login session is used.
Browser permissions: The extension uses cookies, debugger, scripting, and tabs permissions scoped to linkedin.com domains only. See extension/manifest.json for the full permission list.
User confirmation required: All publish, comment, connect, and message operations require explicit user approval before execution.
Network scope: The extension (background.js) connects only to ws://localhost:9335. The Python bridge server (bridge_server.py) binds to 127.0.0.1:9335. Image downloads (image_downloader.py) fetch user-specified URLs via stdlib urllib.request and cache to ~/.linkedin-skills/images. No other outbound network calls are made.
Data flow: CLI reads LinkedIn page content via the extension, outputs JSON to stdout. No data is sent to third-party analytics, telemetry, or remote servers.

Global Constraints

Verify login status before any operation (via check-login).
Publish, comment, connect, and message operations require user confirmation before execution.
File paths must be absolute.
CLI output is JSON, present it in structured format to the user.
Keep operation frequency reasonable to avoid triggering rate limits.

Sub-skill Overview

linkedin-auth — Authentication

Command	Function
`cli.py check-login`	Check login status
`cli.py delete-cookies`	Log out (clear session)

linkedin-publish — Content Publishing

Command	Function
`cli.py submit-post`	Submit a text post
`cli.py submit-image`	Submit an image post

linkedin-explore — Discovery

Command	Function
`cli.py home-feed`	Get home feed posts
`cli.py search`	Search LinkedIn (posts, people, or companies)
`cli.py get-post-detail`	Get post content and comments
`cli.py user-profile`	Get user profile info
`cli.py company-profile`	Get company page info

linkedin-interact — Social Interaction

Command	Function
`cli.py like-post`	Like a post
`cli.py comment-post`	Comment on a post
`cli.py send-connection`	Send a connection request
`cli.py send-message`	Send a direct message

Usage Guidance

This project appears to implement a browser-based LinkedIn automation tool and mostly does what it says, but you should take these precautions before installing: - Review and understand the Chrome extension code (extension/background.js and extension/dom_commands.js). The extension requests cookies and debugger permissions which let it read and manipulate pages in your logged-in LinkedIn session — only install if you trust the code and author. - Confirm the correct local WebSocket port: SKILL.md, bridge.py, background.js and bridge_server.py contain contradictory defaults (9335 vs 9336). Verify the bridge URL in your runtime configuration so the CLI/bridge/extension talk to the same port. - The Python side will download user-specified image URLs to ~/.linkedin-skills/images. If you accept image URLs from others, be aware you are allowing the tool to fetch remote content to your disk. - The tool auto-launches a local bridge server and may try to open Chrome. Consider running the bridge server manually first (python scripts/bridge_server.py) so you can observe connections. - Loading an unpacked extension requires you to enable Developer Mode in Chrome. That is a manual step that grants the extension the listed permissions; do not load it unless you have reviewed the extension source. - If you have stringent security/privacy requirements, prefer not to install code with debugger/cookie access to your browser — instead use an official API integration with explicit credentials. Given the mismatches in documentation vs code and the sensitive browser permissions required, the skill is coherent enough to function but has enough inconsistencies and high-impact capabilities that you should audit the files and runtime port configuration before use.

Capability Analysis

Type: OpenClaw Skill Name: linkedin-skills Version: 1.0.0 The bundle provides a LinkedIn automation suite using a Python CLI and a Chrome extension connected via a local WebSocket bridge (localhost:9336). It supports searching, posting, and social interactions by injecting JavaScript into the browser and using the high-privilege 'debugger' and 'cookies' APIs. While these capabilities are powerful, the code is well-structured, includes human-behavior simulation (rate limiting/delays) to prevent account bans, and explicitly requires user confirmation for impactful actions. No evidence of data exfiltration, hidden remote communication, or malicious intent was found across the Python scripts or the extension's background service worker.

Capability Tags

crypto

Capability Assessment

ℹ Purpose & Capability

The skill claims to automate LinkedIn using the user's logged-in browser session — the included Chrome extension + Python bridge code implements that. Requesting no API keys and using browser cookies is proportionate to the stated purpose. However, registry metadata (no config paths) versus SKILL.md (declares ~/.linkedin-skills/images) and code comments/docs disagree on the bridge port and other minor details, which suggests sloppy packaging rather than clean alignment.

⚠ Instruction Scope

SKILL.md enforces using python scripts/cli.py and a Chrome extension that uses cookies and chrome.debugger to read and manipulate the LinkedIn DOM. That scope is consistent with the purpose, but the runtime instructions contain contradictory details (SKILL.md text mentions bridge at ws://localhost:9335 while extension background.js and bridge_server.py use 9336; bridge.py has a default of 9335 but the CLI passes 9336). The doc also asserts 'no external network calls', but the Python image_downloader deliberately fetches user-supplied image URLs and caches them to ~/.linkedin-skills/images (this is disclosed). Because the extension uses chrome.debugger and cookies, it can access and act inside your logged-in LinkedIn session — appropriate for automation but high-impact if you don't trust the code.

ℹ Install Mechanism

The package doesn't include a formal registry install spec but SKILL.md suggests pip installing websockets or using 'uv sync' (uv package manager). That's an expected moderate-risk install path (pulling from PyPI). There's no remote arbitrary archive download in the install instructions. The extension must be loaded unpacked by the user (manual step) which reduces stealth risk but requires trusting the local extension code.

✓ Credentials

No environment variables or external credentials are requested. The skill requires access to your browser session (cookies) and debugging APIs to operate LinkedIn as your logged-in user — this is proportional to the automation purpose but is sensitive (session access allows acting as you on LinkedIn). The project stores downloaded images under ~/.linkedin-skills/images, which is consistent with its functionality.

✓ Persistence & Privilege

The skill is not marked always:true and does not request to modify other skills. It runs a local WebSocket bridge server and asks you to install a Chrome extension (explicit user action). Those are normal for this architecture; autonomous agent invocation remains enabled by default but is not itself a new red flag here.

Version History

v1.0.0

Initial release: browser-based LinkedIn automation for AI agents

Metadata

Slug linkedin-skills

Version 1.0.0

License MIT-0

All-time Installs 0

Active Installs 0

Total Versions 1

Frequently Asked Questions

What is LinkedIn Skills?

LinkedIn automation skill collection. Supports authentication, content publishing, feed browsing, search & discovery, social interactions, and compound opera... It is an AI Agent Skill for Claude Code / OpenClaw, with 75 downloads so far.

How do I install LinkedIn Skills?

Run "/install linkedin-skills" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is LinkedIn Skills free?

Yes, LinkedIn Skills is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does LinkedIn Skills support?

LinkedIn Skills is cross-platform and runs anywhere OpenClaw / Claude Code is available (darwin, linux).

Who created LinkedIn Skills?

It is built and maintained by quamtumBits (@ceoqveda); the current version is v1.0.0.

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