LinkedIn Jobs

---

name: linkedin_jobs description: Search and monitor LinkedIn job listings with city-based filters, hourly cron support, and smart deduplication. Supports 100+ global tech hubs. metadata: { "openclaw": { "requires": { "bins": ["python"] }, "emoji": "💼", "homepage": "https://clawhub.ai/skills/linkedin-jobs", "install": [{ "id": "pip", "kind": "pip", "packages": ["requests", "beautifulsoup4"], "label": "Install Python dependencies" }] }, "clawhub": { "version": "1.0.0", "license": "MIT", "tags": ["jobs", "linkedin", "scraping", "career", "automation", "cron"], "category": "productivity" } } user-invocable: true

---

LinkedIn Job Search Skill

Search and monitor LinkedIn job listings with powerful filters. Supports 100+ global tech hubs with precise geo IDs, hourly monitoring via cron, and smart deduplication.

Configuration

After installation, optionally customize by copying config.example.json to config.json:

cp {baseDir}/config.example.json {baseDir}/config.json

Configurable options:

Default filters (experience, remote, date_posted)

Scraper delays and timeout

Notification preferences

Custom geo IDs for your cities

Capabilities

1. One-time search: Search LinkedIn for jobs matching keywords and filters 2. Scheduled monitoring: Add search profiles that run hourly via cron 3. Smart deduplication: Only shows new jobs you haven't seen before 4. Global city support: 100+ tech hubs with precise geo IDs

How to Use

One-Time Job Search

Use the exec tool to run a direct search:

python {baseDir}/linkedin_scraper.py --keywords "AI Engineer" --location "Bengaluru, India" --max-pages 2

Parameters:

| Parameter | Description | Example Values | |-----------|-------------|----------------| | --keywords, -k | Job search keywords (required) | "AI Engineer", "Python Developer" | | --location, -l | City, country | "Noida, India", "San Francisco", "Berlin" | | --experience, -e | Experience levels | 2 (Entry), 3 (Associate), 4 (Mid-Senior) | | --remote, -r | Work arrangement | 1 (On-site), 2 (Remote), 3 (Hybrid) | | --date-posted, -d | Time filter | r86400 (24h), r604800 (1wk), r2592000 (1mo) | | --job-type, -j | Employment type | F (Full-time), P (Part-time), C (Contract) | | --max-pages, -p | Pages to scrape (25 jobs/page) | 1-5 |

Example - Entry level AI jobs in Noida, hybrid/on-site:

python {baseDir}/linkedin_scraper.py --keywords "AI Engineer" --location "Noida, India" --experience "2" --remote "1,3" --max-pages 2

Managing Search Profiles (for Hourly Monitoring)

When the user wants to set up recurring job searches, use these commands:

Add a new search profile:

python {baseDir}/linkedin_cron.py add --keywords "AI Engineer" --location "Bengaluru, India"

Add multiple job titles at once (comma-separated):

python {baseDir}/linkedin_cron.py add --keywords "AI Engineer, ML Engineer, Data Scientist" --location "Bengaluru, India"

This creates 3 separate profiles with the same location and filters, and deduplicates results across all of them.

Add with custom filters:

python {baseDir}/linkedin_cron.py add --keywords "Python Developer" --location "San Francisco" --experience "2" --remote "2,3"

List all search profiles:

python {baseDir}/linkedin_cron.py list

Run all enabled profiles now (for hourly cron or manual check):

python {baseDir}/linkedin_cron.py run

Run specific profile:

python {baseDir}/linkedin_cron.py run --profile ai-engineer-bengaluru

Enable/Disable a profile:

python {baseDir}/linkedin_cron.py enable --profile ai-engineer-bengaluru
python {baseDir}/linkedin_cron.py disable --profile ai-engineer-bengaluru

Remove a profile:

python {baseDir}/linkedin_cron.py remove --profile ai-engineer-bengaluru

Clear job history (to see all jobs again):

python {baseDir}/linkedin_cron.py clear-history

View statistics:

python {baseDir}/linkedin_cron.py stats

Supported Cities (100+ Global Tech Hubs)

The skill has built-in geo IDs for precise location-based results:

India: Bengaluru, Noida, Hyderabad, Mumbai, Delhi NCR, Pune, Chennai, Gurugram, Kolkata, Ahmedabad, Jaipur, Chandigarh, Kochi, Coimbatore, Indore, Lucknow

USA: San Francisco, New York, Seattle, Austin, Boston, Los Angeles, Chicago, Denver, San Diego, Washington DC, Atlanta, Dallas, Houston, Phoenix, Miami, Portland

UK: London, Manchester, Edinburgh, Cambridge, Oxford, Bristol, Birmingham, Leeds, Glasgow

Europe: Berlin, Amsterdam, Dublin, Paris, Munich, Zurich, Stockholm, Barcelona, Madrid, Milan, Vienna, Prague, Warsaw, Brussels, Copenhagen

Asia Pacific: Singapore, Sydney, Melbourne, Tokyo, Hong Kong, Seoul, Taipei, Kuala Lumpur, Jakarta, Bangkok, Shanghai, Beijing

Canada: Toronto, Vancouver, Montreal, Ottawa, Calgary, Waterloo

Middle East: Dubai, Abu Dhabi, Riyadh, Tel Aviv, Doha

Latin America: Sao Paulo, Mexico City, Buenos Aires, Bogota, Santiago

Africa: Johannesburg, Cape Town, Lagos, Nairobi, Cairo

For unlisted cities, the skill falls back to text-based search. You can also add custom geo IDs in config.json.

Output Format

The scraper returns JSON with job details including:

title: Job title

company: Company name

location: Job location

employment_type: Full-time, Part-time, Contract, etc.

experience_level: Entry level, Mid-Senior, etc.

posted_date: When the job was posted

requirements: Experience requirements extracted from description

tech_stack: Technologies mentioned (Python, TensorFlow, AWS, etc.)

role_summary: Brief description of the role

url: Direct link to apply

Formatting Job Notifications

When presenting new jobs to the user, format them clearly:

Found X new jobs for "[keywords]":
━━━ [Location] ━━━
1. [Title] @ [Company]
   📍 [Location] ([Remote/Hybrid/On-site])
   💼 [Employment Type] | [Experience Level]
   🕐 Posted [time ago]
   
   📋 Requirements:
   • Experience: [requirements]
   • Tech Stack: [tech_stack]
   • Role: [role_summary]
   
   🔗 [url]

User Intent Mapping

| User Says | Action | |-----------|--------| | "Search LinkedIn for X jobs in Y" | Run one-time search with linkedin_scraper.py | | "Monitor LinkedIn for X jobs" | Add profile with linkedin_cron.py add | | "Add X jobs in Y to my searches" | Add profile with linkedin_cron.py add | | "Search for AI Engineer, ML Engineer, Data Scientist in Bengaluru" | Add multiple profiles with comma-separated keywords | | "Monitor these roles: X, Y, Z in location" | Add multiple profiles at once | | "Stop searching for X" | Disable or remove profile | | "Show my job searches" | Run linkedin_cron.py list | | "Check for new jobs" | Run linkedin_cron.py run | | "Clear job history" | Run linkedin_cron.py clear-history |

Default Filters

When the user doesn't specify filters, use these defaults (configurable in config.json):

Experience: Entry level (code: 2)

Remote: On-site + Hybrid (codes: 1,3)

Date Posted: Last 24 hours (code: r86400)

Max Pages: 2 (~50 jobs)

Filter Code Reference

Experience Levels (--experience):

1 = Internship

2 = Entry level

3 = Associate

4 = Mid-Senior level

5 = Director

6 = Executive

Job Types (--job-type):

F = Full-time

P = Part-time

C = Contract

T = Temporary

I = Internship

Remote Options (--remote):

1 = On-site

2 = Remote

3 = Hybrid

Date Posted (--date-posted):

r86400 = Last 24 hours

r604800 = Last week

r2592000 = Last month

Cron Setup (Optional)

Once you've configured your search profiles, you can ask the agent to set up automated monitoring:

"Run my LinkedIn job searches every hour"

"Check for new jobs every 30 minutes"

"Set up daily job monitoring at 9 AM"

The agent will configure the appropriate cron schedule in OpenClaw based on your preference.

After installation, optionally customize by copying config.example.json to config.json:

cp {baseDir}/config.example.json {baseDir}/config.json

Configurable options:

Default filters (experience, remote, date_posted)

Scraper delays and timeout

Notification preferences

Custom geo IDs for your cities