/linkedin-job-scraper

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](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+):**

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:**

# 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

| 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/