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job-seeker: Skill for Claude Code

.agents/skills/daily/SKILL.md

daily is a skill for Claude Code, Codex from galiprandi/job-seeker. It costs 30 tokens per session (2,830 once invoked), scanned C, original, MIT.

A scheduled job-search routine that checks news, reviews your inbox, and takes action when there has been no recent activity.

In plain words
What is it for?
It checks job-search updates, cleans up related email, and combines news and application tasks once or twice a day.
Why use it?
It keeps your job search moving without requiring you to remember each daily step.

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".

not rated 58repo +11 changed 2d ago C scan SkillSpector: pass 30 tokens original MIT
View source ↗ galiprandi/job-seeker galiprandi.github.io
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/daily/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 daily

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/galiprandi/job-seeker/daily"><img src="https://agentmods.dev/badge/skills/galiprandi/job-seeker/daily.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,830 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 1 finding. 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 $0.00030 $0.02830
Opus 5.5 $0.00012 $0.01132
Sonnet 5.5 $0.00006 $0.00566
Haiku 4.5 $0.00003 $0.00283

Measured 2d ago against content hash 35c085942447, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade C, and why

daily scanned grade C with 1 finding 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 2d 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.

Recursive force deletehighDestructive command

rm -rf with a variable or a broad path is one typo away from removing the wrong tree.

rm -rf .browser-profile/Default/Cache .browser-profile/Default/Code\ Cache .browser-profile/Default/Service\ Worker .browser-profile/Default/GPUCache .browser-profile/GraphiteDawnCache
.agents/skills/daily/SKILL.md · 162 lines

How it starts

The opening of the file, as written. The whole thing — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Daily

Trigger

Keyword: daily

The user says daily (or variants: "routine", "check and apply", "check everything") and the full routine is triggered.

Purpose

Compose the news and apply flows with decision logic to keep the job search active without manual intervention. Designed to run 1-2 times per day.

Pre-flight

  • Verify active LinkedIn and Gmail sessions. If session closed → open browser with wrapper (see AGENTS.md "Browser session"): node .agents/skills/browser-automation/scripts/browser.js open <url> --headed (Gold Rule 5) → notify user → wait for confirmation
  • Browser: always use node .agents/skills/browser-automation/scripts/browser.js for open/close/goto. See AGENTS.md "Browser session" for details. Never call agent-browser open directly, never open Chrome directly
  • 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 strategy (see AGENTS.md "Strategy levels"): 
    node scripts/db.js "SELECT data->'strategy' AS strategy FROM users WHERE id = <user_id>"
    Respect: daily_frequency (on-demand / 1x/day / 2x/day), sources_active (which pillars to activate), apply_batch_size and targets_batch_size (passed to sub-flows). If daily not in sources_active, warn the user

Flow

1. News (check updates)

Run the full news flow:

  • Review Gmail inbox + Job Alerts folder + LinkedIn messages/notifications
  • Classify by fit (Must/Strong/Nice)
  • If there are messages that require a response:
    • Prepare drafts (Gold Rule 6)
    • Present executive summary by priority
    • Wait for user validation
    • Send
  • If no relevant updates: continue to step 2

2. LinkedIn feed scan (hiring posts)

Scan the user's LinkedIn feed for job/hiring posts that fit the profile. The feed re-sorts on every load and new posts surface constantly — run this every daily, even if the last scan was recent.

Read the full file on GitHub · 162 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. 2d ago Changed · +3 lines 35c085942447
  2. 18d ago Changed · +57 lines scan A → C f263358a6e5c
  3. 20d ago Changed · +10 lines 031ca09b2417
  4. 1mo ago Changed 93361a6ace68
  5. 1mo ago First seen · 92 lines · 30 tokens per session scan A 6cb187955b1e

Subscribe to this mod's changes

daily is a skill published in the GitHub repository galiprandi/job-seeker (58 stars, last pushed 2d ago), licensed MIT. It adds 30 tokens to every session and 2,830 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Claude CodeProductivityResearchai-agentsautomationcareerjob-searchlinkedin
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