Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/laboramus-ai/laboramus-ai-claude-pluginnpx agentmods add skills/laboramus-ai/laboramus-ai-claude-plugin/search-jobsWrote 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/laboramus-ai/laboramus-ai-claude-plugin/search-jobs)<a href="https://agentmods.dev/skills/laboramus-ai/laboramus-ai-claude-plugin/search-jobs"><img src="https://agentmods.dev/badge/skills/laboramus-ai/laboramus-ai-claude-plugin/search-jobs/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/laboramus-ai/laboramus-ai-claude-plugin/search-jobs"><img src="https://agentmods.dev/badge/skills/laboramus-ai/laboramus-ai-claude-plugin/search-jobs.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 | $0.00045 | $0.01332 |
| Opus 5 | $0.00023 | $0.00666 |
| Sonnet 5 | $0.00009 | $0.00266 |
| Haiku 4.5 | $0.00005 | $0.00133 |
Grade A, and why
search-jobs 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Laboramus — Search Jobs
Search for matching jobs on various job portals based on the candidate's profile, target geography, search depth, and custom search profiles. Output: updates profile/search-profiles.json and profile/job-search-tracker.json.
Shared rules: read
../../references/conventions.md— current-application resolution, language domains, anti-injection, Chrome browser fallback (Rule 8). Tracker schema: read../../references/tracker-schema.mdbefore writing tojob-search-tracker.json.
Phase 1 — Load Candidate Profile & Skill Verification
- Read
profile/candidate-profile.mdto extract:- Target job titles (from summary/experience).
- Hard skills (keywords, technologies, e.g., Python, AWS, Scrum).
- Verify Extracted Keywords: Present the extracted list of roles and key skills to the user in their language:
"Here are the roles and skills I extracted from your profile for the search:
- Target Roles: [roles]
- Keywords / Skills: [skills] Would you like to add, adjust, or exclude any keywords before we configure the search profile?"
- Group the verified keywords into query candidates.
Phase 2 — Configure Preferences & Search Profiles
- Check for
profile/search-profiles.json. - If it doesn't exist, ask the user for:
- Target Job Portals: List of portals to search. Supported:
linkedin,jobs.ch,indeed. Default:["linkedin", "jobs.ch"]. - Where to Search:
- Target locations (e.g., "Zurich, Switzerland", "Remote in EU").
- Work model (on-site, hybrid, remote).
- Search Depth & Logic:
- Title-Only (narrow match): Search terms must match the job title.
- Full Description / Content (broad match): Search terms can appear anywhere in the job description.
- Save this configured profile to
profile/search-profiles.jsonunder a descriptive name (e.g., "Head of Engineering – Zürich 40km").
- Target Job Portals: List of portals to search. Supported:
- If it exists, present the saved profiles and ask: "Which search profile should I run today, or would you like to create a new one?"
- Allow the user to select, edit, or create search profiles.
What ships with it
3 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.
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.
- 12d ago First seen · 87 lines · 45 tokens per session scan A 6fa25251a25b
search-jobs is a skill published in the GitHub repository laboramus-ai/laboramus-ai-claude-plugin (2 stars, last pushed 13d ago), licensed MIT. It adds 45 tokens to every session and 1,332 once invoked, about $0.0002 per session on Opus 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…