linkedin-job-scraper（linkedin 工作抓取工具）

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.

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

Parameters Reference

Output Columns

The CSV output includes:

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

Error Handling

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/