A terminal-based interface for LinkedIn that enables automated profile scouting, message checking, and feed summarization using session cookies.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install linkedin-cli
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install linkedin-cli using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is LinkedIn CLI?
The LinkedIn CLI, often referred to as lk, is a developer-centric tool designed to bring the power of professional networking directly into the terminal environment. By utilizing session cookies for authentication, it bypasses the need for a standard web browser, allowing users to interact with their network through a fast, text-based interface. As a specialized component within the ecosystem of Openclaw Skills, this tool is perfect for users who value efficiency and want to minimize distractions while managing their professional presence.
This skill is particularly effective for those who need to integrate LinkedIn data into broader automation pipelines. By leveraging the underlying Python-based API wrapper, the LinkedIn CLI provides a witty and punchy experience similar to the popular bird CLI, making it a must-have for any power user looking to expand their Openclaw Skills collection with networking automation.
LinkedIn CLI Use Cases
- Automated profile scouting and data extraction for recruitment or lead generation.
- Quick summarization of the latest feed activity to stay updated without scrolling.
- Checking for new messages and account notifications during terminal-based work sessions.
- Integrating LinkedIn status checks into custom developer dashboards using Openclaw Skills scripts.
How LinkedIn CLI Works
- The user authenticates by extracting active session cookies from a logged-in browser session.
- Environment variables are set to allow the CLI to communicate securely with LinkedIn APIs.
- The lk command-line tool invokes specific Python functions to query the LinkedIn backend.
- Resulting data is parsed and formatted into human-readable text or summaries directly in the console output.
LinkedIn CLI Setup
To get started with this skill, first install the necessary Python dependency:
pip install linkedin-api
Next, you must provide your session cookies. Open LinkedIn in your browser, navigate to DevTools (F12) -> Application -> Cookies, and copy the values for li_at and JSESSIONID. Set them in your environment as follows:
export LINKEDIN_LI_AT="your_li_at_value"
export LINKEDIN_JSESSIONID="your_jsessionid_value"
You can then verify your setup by running lk whoami or lk check to confirm your connection.
LinkedIn CLI Data Schema & Taxonomy
The LinkedIn CLI organizes its operations around session-based authentication and API response mapping. It primarily handles the following data structures:
| Data Component | Format | Description |
|---|---|---|
| Authentication | Environment Vars | Stores li_at and JSESSIONID for session persistence. |
| Profile Data | Text/JSON | Detailed user summaries including public IDs and headlines. |
| Feed Summaries | Ordered List | A collection of the top N posts from the user's timeline. |
| Message Peeks | List | A quick view of recent conversation snippets and sender info. |
LinkedIn CLI Advanced Features
- Deep profile scouting using public IDs to retrieve comprehensive professional backgrounds without browser overhead.
- Feed summarization with configurable depth, allowing users to process large volumes of updates instantly.
- Headless message checking for integration into larger automated notification systems built with Openclaw Skills.
- Minimalist 'check' command that combines profile verification and message status in a single execution.
SKILL.md
Loading
Related Openclaw Skills
Gemini Deep Research
An autonomous AI research agent that decomposes complex queries, crawls the web systematically, and synthesizes multi-source findings into professional reports.
DeepWiki
DeepWiki is an MCP-based skill that allows AI agents to query, browse, and ask questions about public GitHub repository documentation.
Mia Twitter Stealth
A high-stealth Twitter/X automation tool designed to mimic human behavior and bypass bot detection mechanisms using Playwright.
Mia Polymarket Trader
An AI agent designed for autonomous market analysis and trade execution on the Polymarket prediction platform.
Tavily Search
A specialized search engine skill that delivers clean, LLM-ready web data and content extraction for AI agents.
Asura Skill
A comprehensive personality and knowledge skill embodying the legacy of Asura in Krump culture and technology.
Featured*
