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Linkedin Search

CommunityPopular
MadsLorentzen
linkedin-search

Use this skill whenever the user wants to search for jobs in any location or market, find job listings, or look up a specific job posting — in any country, city, or remotely. Invoke for open positions, vacancies, and hiring across any sector or role (software, data, design, marketing, finance, legal, operations, etc.). The location is always supplied explicitly by the user. Trigger phrases: find a job, job search, search for jobs, job openings, vacancies, hiring, positions open, remote jobs, "are there any X jobs in <place>", look up this job posting.

Overview

PublisherMadsLorentzen
Repositoryai-job-search
Skill namelinkedin-search
Stars
46.2K
Forks
15.9K
Bundled files
14
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 14 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by MadsLorentzen on GitHub. Read the source before you install it.

Installation

Install the Linkedin Search AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/MadsLorentzen/ai-job-search/tree/master/.agents/skills/linkedin-search
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/MadsLorentzen/ai-job-search.git /tmp/ai-job-search
mkdir -p .claude/skills
cp -r /tmp/ai-job-search/.agents/skills/linkedin-search .claude/skills/linkedin-search
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Linkedin Search in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Linkedin Search on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Linkedin Search is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

LinkedIn Search Skill

Search live job listings from LinkedIn's public job board for any country/region (and remote). No authentication, no API key, and zero runtime dependencies — it runs with just bun. The location is always passed explicitly, so the same skill works for a forker in any market out of the box.

This is a country-agnostic worked example of the repo's job-portal-skill pattern. LinkedIn's jobs-guest endpoints are global and the HTML parsing is country-independent; only the --location you pass changes per market.

⚠️ Personal use only

This uses LinkedIn's public job pages; automated access is against LinkedIn's Terms of Service, so keep volume low and don't use it commercially or for bulk data collection. Run it on your own responsibility.

When to use this skill

  • Search for job openings in a given location (any country/city) or remotely
  • Filter by recency (posted today / last 7 / 14 / 30 days) or workplace type (remote/hybrid/onsite)
  • Get the full description of a specific job listing

Commands

Search job listings

bash
bun run .agents/skills/linkedin-search/cli/src/cli.ts search --location "<place>" [flags]

Key flags:

  • --location <text> / -l <text> — required. A LinkedIn place string, e.g. "Mumbai, Maharashtra, India", "Berlin, Germany", "London, United Kingdom", or "Remote".
  • --query <text> / -q <text> — keyword search (title, skill, role). Recommended.
  • --jobage <days> — posted within N days: 1, 7, 14, 30. Omit for all postings.
  • --jobage-minutes <n> — posted within N minutes (sub-day precision, e.g. 30). Conflicts with --jobage — pass only one.
  • --remote <mode> — remote, hybrid, or onsite (workplace-type filter).
  • --page <n> — page number (1-indexed, 10 results per page).
  • --limit <n> / -n <n> — cap total results emitted (client-side).
  • --format json|table|plain — default json.

Fetch full job detail

bash
bun run .agents/skills/linkedin-search/cli/src/cli.ts detail <id|url> [--format json|plain]

id is the job ID from search results (e.g. 4426311357). You may also pass a full LinkedIn jobs/view/... URL or a urn:li:jobPosting:... URN. Returns the full description, seniority, employment type, job function, and industries.

Usage examples

bash
# Data engineer roles in Bengaluru, last 30 days
bun run .agents/skills/linkedin-search/cli/src/cli.ts search -q "data engineer" -l "Bengaluru, Karnataka, India" --jobage 30 --format table

# Product manager roles in Berlin, remote
bun run .agents/skills/linkedin-search/cli/src/cli.ts search -q "product manager" -l "Berlin, Germany" --remote remote --format table

# Any role, fully remote
bun run .agents/skills/linkedin-search/cli/src/cli.ts search -q "paralegal" -l "Remote" --format table

# Engineer roles, remote, posted in the last 30 minutes
bun run .agents/skills/linkedin-search/cli/src/cli.ts search -q "engineer" -l "Remote" --jobage-minutes 30 --format table

# Full details for a specific job
bun run .agents/skills/linkedin-search/cli/src/cli.ts detail 4426311357 --format plain

Output formats

FormatBest for
jsonDefault — programmatic use, passing IDs to detail
tableQuick human-readable scanning
plainReading a single job's full detail (detail command)

All errors are written to stderr as { "error": "...", "code": "..." } and the process exits with code 1.

Notes

  • Data is from LinkedIn's public jobs-guest endpoints — no credentials required.
  • Page size is fixed at 10 results per page.
  • LinkedIn may rate-limit; the CLI retries 429/5xx with exponential backoff. Keep volume low (see ToS note above).
  • Job IDs are numeric (e.g. 4426311357) — pass them as-is to detail.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Linkedin Search AI skill do?

Use this skill whenever the user wants to search for jobs in any location or market, find job listings, or look up a specific job posting — in any country, city, or remotely. Invoke for open positions, vacancies, and hiring across any sector or role (software, data, design, marketing, finance, legal, operations, etc.). The location is always supplied explicitly by the user. Trigger phrases: find a job, job search, search for jobs, job openings, vacancies, hiring, positions open, remote jobs, "are there any X jobs in <place>", look up this job posting.

Why use Linkedin Search on TypingMind?

Because you install it once and use it with any model. Linkedin Search is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Linkedin Search in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/MadsLorentzen/ai-job-search/tree/master/.agents/skills/linkedin-search. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Linkedin Search?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Linkedin Search?

As many as you like. As long as a model supports skills, you can use Linkedin Search with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Linkedin Search AI skill free?

Yes. It is published on GitHub by MadsLorentzen under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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