Brightdata SDK
brightdata/skills
Web data extraction and discovery using the Bright Data Python SDK.
Scrapes LinkedIn job postings using the JobSpy library (python-jobspy).
Install Linkedin Job Scraper
$ npx skills add gooseworks-ai/goose-skills --skill linkedin-job-scraper -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install gooseworks-ai/goose-skills linkedin-job-scraper --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/lead-generation/capabilities/linkedin-job-scraper .claude/skills/linkedin-job-scraper && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "linkedin-job-scraper" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/lead-generation/capabilities/linkedin-job-scraper into .claude/skills/linkedin-job-scraper/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkedin-job-scraper", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/gooseworks-ai/goose-skills/tree/main/skills/lead-generation/capabilities/linkedin-job-scraperType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add gooseworks-ai/goose-skills --skill linkedin-job-scraper -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install gooseworks-ai/goose-skills linkedin-job-scraper --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/lead-generation/capabilities/linkedin-job-scraper .agents/skills/linkedin-job-scraper && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "linkedin-job-scraper" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/lead-generation/capabilities/linkedin-job-scraper into .agents/skills/linkedin-job-scraper/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkedin-job-scraper", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add gooseworks-ai/goose-skills --skill linkedin-job-scraper -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install gooseworks-ai/goose-skills linkedin-job-scraper --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/lead-generation/capabilities/linkedin-job-scraper .cursor/skills/linkedin-job-scraper && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "linkedin-job-scraper" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/lead-generation/capabilities/linkedin-job-scraper into .cursor/skills/linkedin-job-scraper/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkedin-job-scraper", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/gooseworks-ai/goose-skills.git --path skills/lead-generation/capabilities/linkedin-job-scraper--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add gooseworks-ai/goose-skills --skill linkedin-job-scraper -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install gooseworks-ai/goose-skills linkedin-job-scraper --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/lead-generation/capabilities/linkedin-job-scraper .gemini/skills/linkedin-job-scraper && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "linkedin-job-scraper" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/lead-generation/capabilities/linkedin-job-scraper into .gemini/skills/linkedin-job-scraper/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkedin-job-scraper", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install gooseworks-ai/goose-skills linkedin-job-scraperInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add gooseworks-ai/goose-skills --skill linkedin-job-scraper -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/lead-generation/capabilities/linkedin-job-scraper .github/skills/linkedin-job-scraper && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "linkedin-job-scraper" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/lead-generation/capabilities/linkedin-job-scraper into .github/skills/linkedin-job-scraper/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkedin-job-scraper", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add gooseworks-ai/goose-skills --skill linkedin-job-scraper -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install gooseworks-ai/goose-skills linkedin-job-scraper --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/lead-generation/capabilities/linkedin-job-scraper .opencode/skills/linkedin-job-scraper && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "linkedin-job-scraper" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/lead-generation/capabilities/linkedin-job-scraper into .opencode/skills/linkedin-job-scraper/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkedin-job-scraper", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
linkedin-job-scraper- GitHub stars
- 1.2k
- Used in
- 1 other repo
- Token cost
- ~1.4k tokens
- SKILL.md length
- 471 words
- Files
- 3 (incl. scripts)
- Skills in repo
- 273
- Repo updated
- First seen
- Licence
- MIT
At a glance
Scrapes LinkedIn job postings using the JobSpy library (python-jobspy).
- Works in 4 steps: Understand the request → Construct the command → Run the script → …
- The user wants to find jobs on LinkedIn
- SKILL.md covers Overview, Quick Start, Workflow and Parameters Reference, plus 4 more sections
- Runs Python scripts from its folder; calls python and pip
What it does
Linkedin Job Scraper is an agent skill from gooseworks-ai/goose-skills. 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.
Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including scripts (for example `scripts/jobspy_scraper.py` and `skill.meta.json`).
It sits in Data & Analytics, covering Web scraping and Go-to-market strategy. It works with LinkedIn and Python. The repository describes itself as: Library of Growth & GTM skills + data APIs for Claude Code, Codex, Cursor to run ads, social, content, lead gen, seo and data scraping. The licence is MIT.
When your agent uses it
- The user wants to find jobs on LinkedIn
- Search for open roles
- Pull job listings
- Build a job pipeline
Example prompts
- “find me some jobs”
- “what roles is [company] hiring for”
- “Use the linkedin-job-scraper skill to scrape LinkedIn job postings using the JobSpy library (python-jobspy)”
- “/linkedin-job-scraper”
Requirements
- Python 3
Workflow steps
4 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit c650c6d. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
pythonpip
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
github.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Linkedin Job Scraper loads about 1.4k tokens when it runs. Until then it costs about 133 tokens; SKILL.md has 471 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from gooseworks-ai/goose-skills at commit c650c6d, republished under its MIT licence (© gooseworks-ai). 471 words, ~1,420 tokens.
Download SKILL.mdSave it as
.claude/skills/linkedin-job-scraper/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.- 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-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
Show full SKILL.md (208 more words)Show less
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/© gooseworks-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 2 other files (scripts) in skills/lead-generation/capabilities/linkedin-job-scraper of gooseworks-ai/goose-skills.
- SKILL.md
- scripts/jobspy_scraper.py
- skill.meta.json
Open the folder on GitHubat commit c650c6d
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in gooseworks-ai/goose-skills, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Linkedin Job Scraper next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Linkedin Job Scraper this skillgooseworks-ai/goose-skills | 1.2k | 1 repos | ~1.4k | Automated safety check: Pass | MIT | |
| Brightdata SDKbrightdata/skills | 264 | — | ~5.2k | Automated safety check: Pass | MIT | |
| Axyusukebe/ax | 719 | 1 repos | ~918 | Automated safety check: Pass | MIT | |
| Facebook Page Postsbrowser-act/skills | 6.1k | — | ~2.3k | Automated safety check: Pass | MIT | |
| Facebook Page Profile Postsbrowser-act/skills | 6.1k | — | ~2.7k | Automated safety check: Pass | MIT | |
| Data Feedsbrightdata/skills | 264 | — | ~2.2k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Linkedin Job Scraper
What does Linkedin Job Scraper do?
Scrapes LinkedIn job postings using the JobSpy library (python-jobspy). Linkedin Job Scraper is an agent skill from gooseworks-ai/goose-skills. Scrapes LinkedIn job postings using the JobSpy library (python-jobspy).
When should I use Linkedin Job Scraper?
Linkedin Job Scraper fits situations like: the user wants to find jobs on LinkedIn; search for open roles; pull job listings; build a job pipeline.
How do I install Linkedin Job Scraper in Claude Code?
Run `npx skills add gooseworks-ai/goose-skills --skill linkedin-job-scraper -a claude-code`. Or copy the skill folder (skills/lead-generation/capabilities/linkedin-job-scraper in gooseworks-ai/goose-skills) into .claude/skills/linkedin-job-scraper in your project. Claude Code loads it when a task matches its description.
How do I install Linkedin Job Scraper in Codex?
Run `npx skills add gooseworks-ai/goose-skills --skill linkedin-job-scraper -a codex`. Or copy the skill folder (skills/lead-generation/capabilities/linkedin-job-scraper in gooseworks-ai/goose-skills) into .agents/skills/linkedin-job-scraper in your project. Codex loads it when a task matches its description.
Can I use Linkedin Job Scraper in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add gooseworks-ai/goose-skills --skill linkedin-job-scraper -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/linkedin-job-scraper, .gemini/skills/linkedin-job-scraper, .github/skills/linkedin-job-scraper and .opencode/skills/linkedin-job-scraper in your project.
What does Linkedin Job Scraper need to run?
Going by SKILL.md and its folder, Linkedin Job Scraper needs Python for the scripts in its folder and the command-line tools its instructions call (python and pip). Our summary lists: Python 3.
Does Linkedin Job Scraper access the network?
SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.
Is Linkedin Job Scraper safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Linkedin Job Scraper use?
Linkedin Job Scraper is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Linkedin Job Scraper use?
About 1.4k tokens (SKILL.md is roughly 5.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Linkedin Job Scraper?
Skills that share tags, products or a category with Linkedin Job Scraper: Brightdata SDK (brightdata/skills, 264 stars), Ax (yusukebe/ax, 719 stars), Facebook Page Posts (browser-act/skills, 6.1k stars) and Facebook Page Profile Posts (browser-act/skills, 6.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Linkedin Job Scraper?
gooseworks-ai (a GitHub organization) maintains it in gooseworks-ai/goose-skills, which has 1,240 GitHub stars. The repository holds 273 skills in this directory. The repository was last updated on October 8, 2026.
Source: gooseworks-ai/goose-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.