Borrowing it
Nothing to install: this file belongs to landedjobs/ai-job-hunt-os. 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/landedjobs/ai-job-hunt-os/main/CLAUDE.mdgit clone --depth 1 https://github.com/landedjobs/ai-job-hunt-osWrote 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/instructions/landedjobs/ai-job-hunt-os/claude-md)<a href="https://agentmods.dev/instructions/landedjobs/ai-job-hunt-os/claude-md"><img src="https://agentmods.dev/badge/instructions/landedjobs/ai-job-hunt-os/claude-md/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/instructions/landedjobs/ai-job-hunt-os/claude-md"><img src="https://agentmods.dev/badge/instructions/landedjobs/ai-job-hunt-os/claude-md.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 | $0.00690 | $0.00690 |
| Opus 5 | $0.00345 | $0.00345 |
| Sonnet 5 | $0.00138 | $0.00138 |
| Haiku 4.5 | $0.00069 | $0.00069 |
Grade A, and why
ai-job-hunt-os CLAUDE.md 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 — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Job Hunt OS: shared context for all skills
These rules apply to every skill in this library. Read them before running any skill.
The user's profile (collect once, reuse everywhere)
The first time any skill runs in a project, check whether a profile.md exists alongside this file. If not, offer to create one by asking:
- Current or most recent role, and the two or three things they are proudest of shipping (with numbers if they have them).
- Target: role family, seniority, company stage (frontier lab / funded startup / big tech AI org), location and remote constraints.
- Constraints that shape advice: visa needs, timeline pressure, comp floor.
Save the answers to profile.md and read it at the start of every skill session. Never make the user repeat their background twice.
Honesty rules (non-negotiable, all skills)
- Never fabricate experience, metrics, employers, dates, or connection points. Not on resumes, not in outreach, not in interview answers.
- Estimates are fine when marked as estimates.
- If the truthful version of the user's background does not clear the bar for a role, say so and point at the gap; do not paper over it with wording.
Evidence labeling (all skills, every claim)
When giving advice or reporting research, label the strength of what you are standing on: measured (a study, platform data, official document), reported (practitioner claim, vendor data, named person's account), or anecdote (one review, one Reddit thread, one candidate's story). When something is unknown (startup financials, a company's interview policy), say "unknown" and suggest how to find out; never fill gaps with confident guesses. This single habit separates these skills from generic career-coach content.
Voice rules for anything written in the user's name
Applies to resumes, outreach, application answers, thank-you notes:
- Write like a person, not a press release. Short sentences are fine. Fragments occasionally.
- No em dashes. No "I hope this finds you well." No "passionate about leveraging."
- Payload first: the specific point before the pleasantries.
- Vary sentence shapes; nothing reads more machine-written than five sentences with identical rhythm.
- Concrete beats grand: "cut eval regressions 40%" beats "drove significant quality improvements."
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 · 51 lines · 690 tokens per session scan A 7b21f42385cb
ai-job-hunt-os CLAUDE.md is an instructions file published in the GitHub repository landedjobs/ai-job-hunt-os (1 stars, last pushed 1mo ago), licensed MIT. It adds 690 tokens to every session, about $0.0034 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.
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