ai-job-search: Skill for Claude Code

.agents/skills/linkedin-search/SKILL.md

linkedin-search is a skill for Claude Code from MadsLorentzen/ai-job-search. It costs 125 tokens per session (1,243 once invoked), scanned A, original, MIT.

A tool for searching LinkedIn's public job listings by place, remote status, posting age, and other filters, and for reading a specific listing.

In plain words
What is it for?
Use it to search for jobs in a country, city, or remote market, filter recent or workplace-specific listings, and retrieve a job description.
Why use it?
It helps find relevant openings without signing in or manually searching LinkedIn pages one at a time.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: installed under .agents/ (shared by several agents).

This is MadsLorentzen/ai-job-search's own configuration. It tells Claude Code how to work on ai-job-search itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything ai-job-search configures →

About the project

AI Job Search is a Claude Code-based framework that runs on a user's machine to organize an AI-assisted job application process. It evaluates job postings, adapts CVs, writes cover letters, and helps prepare for interviews. The catalogue entries define commands, skills, instructions, an agent, and a setting for this workflow.

MadsLorentzen/ai-job-search · 47,502 stars · on GitHub

Reuse

Borrowing it

Nothing to install: this file belongs to MadsLorentzen/ai-job-search. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/MadsLorentzen/ai-job-search/master/.agents/skills/linkedin-search/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/MadsLorentzen/ai-job-search

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for linkedin-search

README.md
[![agentmods](https://agentmods.dev/badge/skills/madslorentzen/ai-job-search/linkedin-search/github.svg)](https://agentmods.dev/skills/madslorentzen/ai-job-search/linkedin-search)
Your own site
<a href="https://agentmods.dev/skills/madslorentzen/ai-job-search/linkedin-search"><img src="https://agentmods.dev/badge/skills/madslorentzen/ai-job-search/linkedin-search/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for linkedin-search

Your own site · 80×15
<a href="https://agentmods.dev/skills/madslorentzen/ai-job-search/linkedin-search"><img src="https://agentmods.dev/badge/skills/madslorentzen/ai-job-search/linkedin-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 125 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,243 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Snyk warn 7 Sept 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00125 $0.01243
Opus 5.5 $0.00050 $0.00497
Sonnet 5.5 $0.00025 $0.00249
Haiku 4.5 $0.00013 $0.00124

Measured 1mo ago against content hash f7d0a742b12c, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

linkedin-search scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

The scan reads SKILL.md. This mod also ships 11 executable files (cli/src/cli.ts, cli/src/commands/detail.ts, cli/src/commands/search.ts, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

3 near-identical copies found in the catalogue:

.agents/skills/linkedin-search/SKILL.md · 104 lines

How it starts

The opening of the file, as written. The whole thing — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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

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

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

Read the full file on GitHub · 104 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 104 lines · 125 tokens per session scan A f7d0a742b12c

Subscribe to this mod's changes

linkedin-search is a skill published in the GitHub repository MadsLorentzen/ai-job-search (47,502 stars, last pushed today), licensed MIT. It adds 125 tokens to every session and 1,243 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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