linkedin-job-scraper
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.
Best use case
linkedin-job-scraper is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using linkedin-job-scraper should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/linkedin-job-scraper/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How linkedin-job-scraper Compares
| Feature / Agent | linkedin-job-scraper | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# LinkedIn Scraper ## Overview This skill finds LinkedIn job postings by running `tools/jobspy_scraper.py`, a thin wrapper around the [JobSpy](https://github.com/speedyapply/JobSpy) library. It handles installation, parameter construction, execution, and result interpretation. ## Quick Start **Install the dependency once (requires Python 3.10+):** ```bash python3.12 -m pip install -U python-jobspy --break-system-packages ``` **Run the scraper:** ```bash 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. ```bash 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:** ```bash 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:** ```bash # 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:** ```bash 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/`: ```bash cp skills/linkedin-job-scraper/scripts/jobspy_scraper.py tools/ ```
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