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 instructions/ledq/resumery/claude-mdgit clone --depth 1 https://github.com/ledq/resumeryWrote 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/ledq/resumery/claude-md)<a href="https://agentmods.dev/instructions/ledq/resumery/claude-md"><img src="https://agentmods.dev/badge/instructions/ledq/resumery/claude-md.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 | $0.00308 | $0.00308 |
| Opus 5 | $0.00154 | $0.00154 |
| Sonnet 5 | $0.00062 | $0.00062 |
| Haiku 4.5 | $0.00031 | $0.00031 |
Grade A, and why
resumery 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 4d 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.
What it actually says
Resume Tailoring
Tailors the candidate's resume to one job description (JD) per run. Each run lives in its
own application workspace (applications/<id>/). Agents author resume content as JSON
(the workspace's resume.json). The candidate's real experience lives in
bank/experience_bank.md, the only source of facts.
Objective
Surface and frame the candidate's experience to match the JD as fully as the evidence allows, and not one claim further: maximum truthful match. The edge is a rich evidence bank, not a flat resume, so there is more true material to surface than a one-page resume could show.
The Rule: claim vs. framing
- Claims are checkable facts: titles, employers, dates, degrees, credentials, whether an accomplishment happened. They must be true; this record layer has zero degrees of freedom.
- Framing is how true work is presented: which skills lead, which bullets are chosen, the words describing real work. Optimize it freely, limited only by truth.
Every claim on the resume must trace to the bank. Reframing real experience to fit the JD is the job; inventing experience, outcomes, or numbers is the one thing never allowed.
Punctuation
No em dashes (the "—" character). Join clauses with semicolons, set off asides with commas, introduce with colons. Spell out the "~" shorthand ("about").
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.
- 4d ago First seen · 28 lines · 308 tokens per session scan A e263d005193d
resumery CLAUDE.md is an instructions file published in the GitHub repository ledq/resumery (1 stars, last pushed 1mo ago), licensed MIT. It adds 308 tokens to every session, about $0.0015 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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