| name | linkedin-job-scraper |
| description | Scrapes LinkedIn job postings using the JobSpy library (python-jobspy). Use this skill whenever the user wants to find jobs on LinkedIn, search for open roles, pull job listings, build a job pipeline, source job targets for GTM research, or monitor hiring signals. Even if the user just says "find me some jobs" or "what roles is [company] hiring for", use this skill. It runs a local Python script that outputs a CSV of job postings with title, company, location, salary, job type, description, and direct URLs.
|
| tags | ["lead-generation"] |
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
| 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 |
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 |
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:
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
| 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 |
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/
