gooseworks-ai/linkedin-job-scraper

LinkedIn Scraper

Overview

This skill finds LinkedIn job postings by running tools/jobspy_scraper.py, a thin wrapper around the JobSpy library. It handles installation, parameter construction, execution, and result interpretation.

Quick Start

Install the dependency once (requires Python 3.10+):

python3.12 -m pip install -U python-jobspy --break-system-packages

Run the scraper:

python3.12 tools/jobspy_scraper.py \
  --search "software engineer" \
  --location "San Francisco, CA" \
  --results 25 \
  --output .tmp/jobs.csv

Results are saved as CSV and printed as a summary table.

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Workflow

Step 1 — Understand the request

Identify from the user's message:

• Search term — job title, role, or keyword (required)
• Location — city, state, or "Remote" (optional but recommended)
• Results wanted — default to 25 if not specified
• Recency — hours_old filter if user wants recent posts (e.g. "last 48 hours")
• Company filter — linkedin_company_ids if targeting a specific company
• Full descriptions — set --fetch-descriptions if user needs job description text

If anything is ambiguous (e.g. "find AI jobs"), pick reasonable defaults and tell the user what you used.

Step 2 — Construct the command

Build the tools/jobspy_scraper.py command using the parameters below. Always save output to .tmp/ so it's disposable and easy to find.

python tools/jobspy_scraper.py \
  --search "<term>" \
  --location "<location>" \
  --results <N> \
  [--hours-old <N>] \
  [--fetch-descriptions] \
  [--company-ids <id1,id2>] \
  [--job-type fulltime|parttime|contract|internship] \
  [--remote] \
  --output .tmp/<descriptive_filename>.csv

Note: --hours-old and --easy-apply cannot be used together (LinkedIn API constraint).

Step 3 — Run the script

Execute the command. The script will print a progress message and a summary of results found.

If the script is not found at tools/jobspy_scraper.py, check whether the file needs to be created by reading skills/linkedin-job-scraper/scripts/jobspy_scraper.py and copying it to tools/.

Step 4 — Interpret and present results

After the run:

• Report how many jobs were found
• Show a brief table: Title | Company | Location | Salary | Posted
• Note the output file path so the user can open it
• If 0 results: suggest broadening the search term or removing the location filter

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Parameters Reference

| Flag | Description | Default | |------|-------------|---------| | --search | Job title / keywords | required | | --location | City, state, or country | none | | --results | Number of results to fetch | 25 | | --hours-old | Only jobs posted within N hours | none | | --fetch-descriptions | Fetch full job descriptions (slower) | false | | --company-ids | Comma-separated LinkedIn company IDs | none | | --job-type | fulltime, parttime, contract, internship | any | | --remote | Filter for remote jobs only | false | | --output | Path for CSV output | .tmp/jobs.csv |

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Output Columns

The CSV output includes:

| Column | Description | |--------|-------------| | TITLE | Job title | | COMPANY | Employer name | | LOCATION | City / State / Country | | IS_REMOTE | True/False | | JOB_TYPE | fulltime, contract, etc. | | DATE_POSTED | When the listing was posted | | MIN_AMOUNT | Minimum salary | | MAX_AMOUNT | Maximum salary | | CURRENCY | Currency code | | JOB_URL | Direct link to the LinkedIn posting | | DESCRIPTION | Full job description (if --fetch-descriptions used) | | JOB_LEVEL | Seniority level (LinkedIn-specific) | | COMPANY_INDUSTRY | Industry classification |

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Common Use Cases

Find recent engineering roles at a startup:

python tools/jobspy_scraper.py --search "growth engineer" --location "New York" \
  --results 50 --hours-old 72 --output .tmp/growth_eng_nyc.csv

Monitor what a specific company is hiring for:

# First find the LinkedIn company ID from the company's LinkedIn URL
python tools/jobspy_scraper.py --search "engineer" --company-ids 1234567 \
  --results 100 --fetch-descriptions --output .tmp/company_hiring.csv

Find remote contract roles:

python tools/jobspy_scraper.py --search "data analyst" --remote \
  --job-type contract --results 30 --output .tmp/remote_contracts.csv

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Error Handling

| Error | Fix | |-------|-----| | ModuleNotFoundError: jobspy | Run pip install -U python-jobspy | | 0 results returned | Broaden search term, remove location, increase --results | | Rate limited / blocked | Wait a few minutes; avoid running back-to-back large scrapes | | hours_old and easy_apply cannot both be set | Remove one of those flags |

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Script Location

The scraper script lives at tools/jobspy_scraper.py.

If it doesn't exist, copy it from skills/linkedin-scraper/scripts/jobspy_scraper.py to tools/:

cp skills/linkedin-job-scraper/scripts/jobspy_scraper.py tools/