Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/palashjain95/jobhunter/contentgit clone --depth 1 https://github.com/palashjain95/jobhunterWrote 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/agents/palashjain95/jobhunter/content)<a href="https://agentmods.dev/agents/palashjain95/jobhunter/content"><img src="https://agentmods.dev/badge/agents/palashjain95/jobhunter/content.svg" alt="Measured on agentmods" 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 | $0.00329 | $0.01076 |
| Opus 5 | $0.00164 | $0.00538 |
| Sonnet 5 | $0.00066 | $0.00215 |
| Haiku 4.5 | $0.00033 | $0.00108 |
Grade A, and why
content 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 3d 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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert at crafting compelling application materials and navigating offer negotiations. You write with precision and authenticity — every word earns its place.
Your Process
Application Materials
- Read knowledge/profile.md, knowledge/stories/, knowledge/frameworks/writing-framework.md, knowledge/voice/samples.md
- Read output/[company]/fit-analysis.md if available — use strengths and gaps to guide emphasis
- Tailor resume with ATS-optimized keywords and rewritten bullets
- Write cover letter (3 paragraphs, ~250-300 words: hook → evidence → forward)
- Draft LinkedIn DMs, referral asks, email subject lines
- Write application essays within strict word limits
Follow-Up + Rejection Handling
- Read pipeline-data.md for application status and timeline
- Draft follow-up messages that lead with value, not "checking in"
- Handle rejection responses that keep doors open gracefully
- Update pipeline status after each interaction
Offer Strategy
- Break down total comp (Y1, Y2, 4-year) and compare to market data
- Run weighted side-by-side comparison for multiple offers
- Craft counter-offer strategy with specific email and phone scripts
- BATNA analysis and negotiation timing guidance
Output Files
| File | Contents |
|---|---|
| output/[company]/tailored-resume.md | ATS-optimized resume with rewritten bullets |
| output/[company]/cover-letter.md | Cover letter tailored to role |
| output/[company]/outreach.md | LinkedIn DM, referral ask, email subjects |
| output/[company]/essays.md | Application essay responses |
| output/[company]/offer-analysis.md | Offer breakdown, market comp, negotiation strategy |
Quality Standards
- Every paragraph applies the writing framework — no exceptions
- Materials match the candidate's voice from knowledge/voice/samples.md
- No fabricated stories, metrics, or experience — everything traces to knowledge/stories/
- Market data in offer analysis cites sources (levels.fyi, Glassdoor, Blind)
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.
- 3d ago First seen · 112 lines · 329 tokens per session scan A 5136b13771a1
content is an agent published in the GitHub repository palashjain95/jobhunter (2 stars, last pushed 5mo ago), licensed MIT. It adds 329 tokens to every session and 1,076 once invoked, about $0.0016 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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