job-seeker: Skill for Claude Code

.agents/skills/radar/SKILL.md

radar is a skill for Claude Code, Codex from galiprandi/job-seeker. It costs 42 tokens per session (2,403 once invoked), scanned A, original, MIT.

An alert setup for job boards, technology-company career sites, and target-company hiring systems, which are the websites used to list and manage job openings.

In plain words
What is it for?
It registers job-search alerts, monitors selected companies and career sites, and routes incoming alerts into a dedicated Gmail folder.
Why use it?
It brings new opportunities to you automatically instead of requiring repeated manual searches.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents); mentions AGENTS.md.

This is galiprandi/job-seeker's own configuration. It tells Claude Code and Codex how to work on job-seeker 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 job-seeker configures →

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is node scripts/db.js "SELECT category, key, value, confidence, source FROM preferences WHERE user_id = <user_id> AND status = 'active' ORDER BY category, key".

Reuse

Borrowing it

Nothing to install: this file belongs to galiprandi/job-seeker. 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/galiprandi/job-seeker/main/.agents/skills/radar/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/galiprandi/job-seeker

Made for: Claude Code, Codex.

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 radar

README.md
[![agentmods](https://agentmods.dev/badge/skills/galiprandi/job-seeker/radar/github.svg)](https://agentmods.dev/skills/galiprandi/job-seeker/radar)
Your own site
<a href="https://agentmods.dev/skills/galiprandi/job-seeker/radar"><img src="https://agentmods.dev/badge/skills/galiprandi/job-seeker/radar/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 radar

Your own site · 80×15
<a href="https://agentmods.dev/skills/galiprandi/job-seeker/radar"><img src="https://agentmods.dev/badge/skills/galiprandi/job-seeker/radar.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,403 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
  • 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 $0.00042 $0.02403
Opus 5 $0.00021 $0.01202
Sonnet 5 $0.00008 $0.00481
Haiku 4.5 $0.00004 $0.00240

Measured yesterday against content hash f511755274cf, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

radar 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 yesterday.

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.

.agents/skills/radar/SKILL.md · 166 lines

How it starts

The opening of the file, as written. The whole thing — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Radar

Trigger

Keyword: radar

The user says radar (or variants: "set up alerts", "register on platforms", "new platforms") and the registration + alert configuration + career site alerts + Gmail filter flow is triggered.

Purpose

Passive sourcing: platforms and career sites bring opportunities to the user without having to search manually. Alerts arrive in a Job Alerts folder in Gmail, and the news skill consumes them when the user says news.

Three alert sources:

  1. Job boards (Otta, Torre, Built In, etc.) — broad reach
  2. Big tech career sites (Google, Meta, Amazon, etc.) — high-value companies not in the 40 targets
  3. Target company ATS alerts (configured during targets flow registration) — deep monitoring of the 40 target companies

Flow

0. Pre-flight

  • Verify active Gmail session. If session closed → open browser with wrapper (see AGENTS.md "Browser session"): node scripts/browser.js open <url> --headed (Gold Rule 5)
  • Browser: always use node scripts/browser.js for open/close/goto. See AGENTS.md "Browser session" for details. Never call playwright-cli open directly, never open Chrome directly
  • Read PLATFORMS.md "Alert Tracking" section to see which platforms need configuration
  • Read PROFILE.md to get keywords, seniority, location, preferences
  • Load active preferences (see memory skill):
    node scripts/db.js "SELECT category, key, value, confidence, source FROM preferences WHERE user_id = <user_id> AND status = 'active' ORDER BY category, key"
    
  • Load target companies (companies loaded from users.data.target_companies in DB, each {name, url, sector}). These are priority targets for alert configuration and platform prioritization:
    node scripts/db.js "SELECT data->'target_companies' AS target_companies FROM users WHERE id = <user_id>"
    

1. Register on platforms

For each unconfigured platform (column "Profile" = "—"):

  • Navigate to the platform
  • Login with Google when possible (preferred). If no Google login → open browser with wrapper (node scripts/browser.js open <url> --headed) and ask user to login manually (Gold Rule 5)
  • Complete minimum profile:
    • First name, last name
    • Title / headline (from PROFILE.md)
    • Location (from PROFILE.md)
    • Seniority (from PROFILE.md)
    • Upload CV (CV path in DB or .env)
    • Preferences: remote, full-time, USD salary range
  • Mark "Profile" = "✅" in PLATFORMS.md

Read the full file on GitHub · 166 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. yesterday Changed f511755274cf
  2. 12d ago First seen · 166 lines · 42 tokens per session scan A cdef6d7c9142

Subscribe to this mod's changes

radar is a skill published in the GitHub repository galiprandi/job-seeker (26 stars, last pushed yesterday), licensed MIT. It adds 42 tokens to every session and 2,403 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 2026-08-30.