Borrowing it
Nothing to install: this file belongs to pedrolucazx/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.
curl -O https://raw.githubusercontent.com/pedrolucazx/job-search/main/.agents/skills/linkedin-search/SKILL.mdgit clone --depth 1 https://github.com/pedrolucazx/job-searchWrote 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.
[](https://agentmods.dev/skills/pedrolucazx/job-search/linkedin-search)<a href="https://agentmods.dev/skills/pedrolucazx/job-search/linkedin-search"><img src="https://agentmods.dev/badge/skills/pedrolucazx/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.
<a href="https://agentmods.dev/skills/pedrolucazx/job-search/linkedin-search"><img src="https://agentmods.dev/badge/skills/pedrolucazx/job-search/linkedin-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00125 | $0.01134 |
| Opus 5.5 | $0.00050 | $0.00454 |
| Sonnet 5.5 | $0.00025 | $0.00227 |
| Haiku 4.5 | $0.00013 | $0.00113 |
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.
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.
This is a copy
95% identical to linkedin-search — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 99 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-guestendpoints are global and the HTML parsing is country-independent; only the--locationyou 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.--remote <mode>—remote,hybrid, oronsite(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— defaultjson.
Fetch full job detail
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, industries, and apply link.
What ships with it
13 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- cli/bun.lock 1.1 KB
- cli/package.json 577 B
- cli/README.md 2.3 KB
- cli/src/cli.ts 5.1 KB runs code
- cli/src/commands/detail.ts 1.7 KB runs code
- cli/src/commands/search.ts 2.3 KB runs code
- cli/src/helpers.ts 8.0 KB runs code
- cli/tests/cli-flag-validation.test.ts 3.1 KB runs code
- cli/tests/helpers.ts 959 B runs code
- cli/tests/parsing.test.ts 2.3 KB runs code
- cli/tests/search.test.ts 1.2 KB runs code
- cli/tsconfig.json 305 B
- url-reference.md 1.5 KB
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.
- 1mo ago First seen · 99 lines · 125 tokens per session scan A 471f2df401e1
linkedin-search is a skill published in the GitHub repository pedrolucazx/job-search (5 stars, last pushed 18d ago), licensed MIT. It adds 125 tokens to every session and 1,134 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 95% identical to linkedin-search, differing in 7 lines, and is treated as a copy.
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