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.
curl -O https://raw.githubusercontent.com/galiprandi/job-seeker/main/.agents/skills/radar/SKILL.mdgit clone --depth 1 https://github.com/galiprandi/job-seekerWrote 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/galiprandi/job-seeker/radar)<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.
<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>- NVIDIA SkillSpector pass
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 | $0.00042 | $0.02403 |
| Opus 5 | $0.00021 | $0.01202 |
| Sonnet 5 | $0.00008 | $0.00481 |
| Haiku 4.5 | $0.00004 | $0.00240 |
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.
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:
- Job boards (Otta, Torre, Built In, etc.) — broad reach
- Big tech career sites (Google, Meta, Amazon, etc.) — high-value companies not in the 40 targets
- Target company ATS alerts (configured during
targetsflow 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.jsfor open/close/goto. See AGENTS.md "Browser session" for details. Never callplaywright-cli opendirectly, never open Chrome directly - Read
PLATFORMS.md"Alert Tracking" section to see which platforms need configuration - Read
PROFILE.mdto get keywords, seniority, location, preferences - Load active preferences (see
memoryskill):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
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.
- yesterday Changed f511755274cf
- 12d ago First seen · 166 lines · 42 tokens per session scan A cdef6d7c9142
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.
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