Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/ledq/resumerynpx agentmods add skills/ledq/resumery/tailorWrote 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/ledq/resumery/tailor)<a href="https://agentmods.dev/skills/ledq/resumery/tailor"><img src="https://agentmods.dev/badge/skills/ledq/resumery/tailor/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/ledq/resumery/tailor"><img src="https://agentmods.dev/badge/skills/ledq/resumery/tailor.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 | $0.00054 | $0.01124 |
| Opus 5.5 | $0.00022 | $0.00450 |
| Sonnet 5.5 | $0.00011 | $0.00225 |
| Haiku 4.5 | $0.00005 | $0.00112 |
Grade A, and why
tailor 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 1mo 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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/tailor: front door for the tailoring pipeline
Resolve WHICH JD the user means, confirm it really is a job posting, mint the application workspace, hand the engine the workspace, and relay the result. The file on disk is always the canonical text: you read the JD to judge it, but the copy the pipeline receives is the file's.
1. Mint the staging namespace: FIRST, once
mktemp -d /tmp/jd_stage.XXXXXX
It prints the run's namespace directory (call it <dir>). This is the ONLY randomness
in staging, minted once; every step below uses fixed names inside it (<dir>/jd.txt,
<dir>/url). Always a fresh mktemp -d: a fixed path is shared mutable state, and a
leftover from an earlier run would silently tailor the resume to a stale JD.
2. Fill it: every source becomes <dir>/jd.txt
From $ARGUMENTS (and, if it is empty, the conversation):
- A URL → fetch into the namespace deterministically:
Exit 0 → the posting is atpython3 ops/jd_fetch.py '<url>' <dir><dir>/jd.txt(the URL lands at<dir>/url, where step 4's script reads it for identity; not your concern after this command). Exit 4 → the page is JS-rendered or blocked the fetch: tell the user and ask them to paste the posting text instead. - A saved application (an
applications/<id>path or id) → no staging; the folder already holds the posting. Useapplications/<id>/jd.txtas the JD path in the steps below. (Step 4's identity check will match and reuse the folder; this is how a saved or previously tailored posting is re-tailored.) - A path to a JD file the user already has → copy it in:
cp '<their file>' <dir>/jd.txt. - Raw posting text (in the argument, or pasted earlier in this conversation) →
use the Write tool to put the posting at
<dir>/jd.txt, VERBATIM: one copy, change nothing, drop nothing. - Ambiguous (several JDs in this chat, or none anywhere) → ask the user which posting they mean, or for the posting itself. Do not guess.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 94 lines · 54 tokens per session scan A 4fcf8acbcfd2
tailor is a skill published in the GitHub repository ledq/resumery (1 stars, last pushed 18d ago), licensed MIT. It adds 54 tokens to every session and 1,124 once invoked, about $0.0002 per session on Opus 5.5. 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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