AGENT SKILLBY ATHINA-AI
LinkedIn job scraper
AT A GLANCE
LinkedIn job scraper is a social media skill for AI agents. This skill finds LinkedIn job postings by running tools/jobspyscraper.py, a thin wrapper around the JobSpy library. The athina-ai/goose-skills repository on GitHub, maintained by athina-ai, has 912 stars and the MIT license. To add it, run npx skills add athina-ai/goose-skills --skill linkedin-job-scraper
- SOURCE REPOSITORY
- athina-ai/goose-skills (opens GitHub in a new tab)
- REPO STARS
- SOURCE REPOSITORY
- LICENSE
- MIT
- CATEGORIES
- SKILL.MD SIZE
- 5 KB160 LINES
QUICK ANSWER
- WHAT IT IS01
- This skill finds LinkedIn job postings by running tools/jobspyscraper.py, a thin wrapper around the JobSpy library. The value is a focused slice of social content judgment, useful when several similar skills cover the same ground.
- INPUTS02
- Context for social content: your goals, audience, constraints, and any source material the skill asks for.
- OUTPUT03
- A ready-to-use result for social content: the analysis, copy, or recommendations the agent produces.
INSTALL
One command adds this skill from its source repository.
npx skills add athina-ai/goose-skills --skill linkedin-job-scraperREAD THE SKILL.MD BELOW BEFORE YOU RUN IT. SKILLS INSTRUCT YOUR AGENT.
SKILL.MD
The full file, as published in the source repository. Copy it, download it or open it on GitHub.
ON THIS PAGE · 12
LinkedIn Scraper#
Overview#
This skill finds LinkedIn job postings by running tools/jobspy_scraper.py, a thin wrapper
around the JobSpy (opens in a new tab) 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-packagesRun the scraper:
python3.12 tools/jobspy_scraper.py \
--search "software engineer" \
--location "San Francisco, CA" \
--results 25 \
--output .tmp/jobs.csvResults 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_oldfilter if user wants recent posts (e.g. "last 48 hours") - Company filter —
linkedin_company_idsif targeting a specific company - Full descriptions — set
--fetch-descriptionsif 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>.csvNote: --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.csvMonitor 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.csvFind remote contract roles:
python tools/jobspy_scraper.py --search "data analyst" --remote \
--job-type contract --results 30 --output .tmp/remote_contracts.csvError 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/FAQ
07 QUESTIONS
01What is the LinkedIn job scraper agent skill?
This skill finds LinkedIn job postings by running tools/jobspyscraper.py, a thin wrapper around the JobSpy library. It is listed under social media in the 100xLab agent skills directory.
02How do I install LinkedIn job scraper in Cursor, Claude Code, or Codex?
Run npx skills add athina-ai/goose-skills --skill linkedin-job-scraper in the project where you want it, then ask your agent for the skill by name. The --skill flag installs only LinkedIn job scraper, not every skill in the repository.
03What does the LinkedIn job scraper SKILL.md cover?
The SKILL.md includes sections on Overview, Quick Start, Workflow, Step 1 — Understand the request, Step 2 — Construct the command and Step 3 — Run the script. Read the full text on this page or in plain markdown at /resources/agent-skills/athina-ai-goose-skills--linkedin-job-scraper--3qt8gz/raw.
04Which agents can use LinkedIn job scraper?
LinkedIn job scraper installs with the cross-agent skills installer (npx skills add), which sets it up for agents such as Claude Code, Cursor and Codex. Each agent loads the SKILL.md when you ask for the skill by name.
05What license is LinkedIn job scraper under?
The athina-ai/goose-skills repository declares the MIT license. Read the license file in the repository before you copy or redistribute the skill.
06Is LinkedIn job scraper free to use?
Reading, copying and installing LinkedIn job scraper costs nothing: it is published in a public GitHub repository under the MIT license. Reuse and redistribution follow that license.
07Where is the source of LinkedIn job scraper?
LinkedIn job scraper comes from https://github.com/athina-ai/goose-skills, which has 912 GitHub stars. The SKILL.md is at https://github.com/athina-ai/goose-skills/blob/HEAD/skills/lead-generation/capabilities/linkedin-job-scraper/SKILL.md. The author is athina-ai.
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ATTRIBUTION
LinkedIn job scraper was written by its original authors and is published in athina-ai/goose-skills (opens GitHub in a new tab) under the MIT license. All rights stay with the original authors.
100xLab did not write, maintain or endorse this skill. This page lists it for discovery. Repo stars belong to the source repository, not to the skill. Review any skill before you install it.