A sophisticated automation tool for AI agents to search for and submit LinkedIn Easy Apply job applications using Puppeteer and verified resume data.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install linkedin-easy-apply-automation
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-easy-apply-automation 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 Easy Apply Automation?
This skill empowers AI coding agents to automate the tedious process of job hunting on LinkedIn. By utilizing Puppeteer and a persistent Chromium profile, the skill can navigate search filters, identify relevant roles, and handle the multi-step Easy Apply process. It is designed to be a cornerstone of the Openclaw Skills ecosystem for career management, focusing on high-volume, remote-first job searches.
The automation prioritizes safety and accuracy, ensuring that no fabricated facts are submitted. It uses a conservative answering logic that only provides data verified within the user's resume PDF or explicit instructions, making it a reliable choice for developers and professionals looking to scale their job application reach without compromising their professional integrity.
LinkedIn Easy Apply Automation Use Cases
- Automating the daily search for niche roles like AI Engineer, LLM Specialist, or Full-stack Developer.
- Submitting remote-only job applications at scale using a verified resume PDF.
- Tracking application history via stateful logging to avoid duplicate submissions across multiple sessions.
- Filtering job listings specifically for Easy Apply eligibility to maximize application velocity.
How LinkedIn Easy Apply Automation Works
- The AI agent initializes a Puppeteer browser instance using a persistent user data directory to maintain LinkedIn login sessions.
- It generates targeted search URLs with specific parameters for Easy Apply filters, keywords, and location constraints.
- The skill identifies job IDs and attempts to open the direct application modal using specialized Openclaw Skills URL patterns.
- It uploads the resume PDF and parses application forms step-by-step, filling in radio buttons and text fields based on resume-backed facts.
- The workflow implements a safety check to skip questions involving compensation, custom essays, or unverified information.
- Upon successful submission, the job ID is recorded in a local state file to ensure it is not processed in future runs.
LinkedIn Easy Apply Automation Setup
To get started with this skill in your Openclaw Skills environment, configure the necessary environment variables and ensure Puppeteer is available.
# Define paths and search criteria
export RESUME_PDF="/absolute/path/to/resume.pdf"
export CHROME_PROFILE="$HOME/.cache/linkedin-chrome"
export SEARCHES="AI Engineer|Full Stack|Node.js"
export LOCATION="United States"
export REMOTE_ONLY=1
# Install dependencies
npm install puppeteer
LinkedIn Easy Apply Automation Data Schema & Taxonomy
The skill manages persistent data to maintain the workflow's state and provide detailed reporting.
| File Path | Format | Description |
|---|---|---|
/tmp/linkedin-easyapply-daily/state.json |
JSON | Tracking of seen, applied, and skipped Job IDs. |
/tmp/linkedin-easyapply-daily/results.jsonl |
JSONL | Detailed logs for every application attempt and error. |
RESUME_PDF |
The primary source of truth for all applicant facts. |
LinkedIn Easy Apply Automation Advanced Features
- Stateful Daily Reruns: Uses local JSON state to ensure the agent never applies to the same job twice.
- Conservative Answer Guardrails: Automatically skips application steps that require subjective input or sensitive compensation data.
- Direct Modal Navigation: Attempts to bypass UI lag by navigating directly to LinkedIn's internal apply flow URLs.
- Multi-Agent Support: Compatible with a wide range of agents including Claude Code, Cursor, and Roo Code within the Openclaw Skills framework.
- Headless-Optional Execution: Supports running with a visible browser for manual intervention or debugging.
SKILL.md
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