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/setupWrote 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/setup)<a href="https://agentmods.dev/skills/ledq/resumery/setup"><img src="https://agentmods.dev/badge/skills/ledq/resumery/setup/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/setup"><img src="https://agentmods.dev/badge/skills/ledq/resumery/setup.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 | $0.00062 | $0.00267 |
| Opus 5.5 | $0.00025 | $0.00107 |
| Sonnet 5.5 | $0.00012 | $0.00053 |
| Haiku 4.5 | $0.00006 | $0.00027 |
Grade B, and why
setup scanned grade B 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 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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
sudo or an interactive prompt, so never run the install yourself. Once they say it is What it actually says
/setup: environment check
Run the deterministic checker and relay its result:
python3 ops/env_check.py
- Everything present (exit 0): tell the user they are ready, and point at the next
step: put existing resumes into
bank/sources/and run/onboard(or, if the bank already exists,/tailor <posting>). - Something missing (exit 4): show the install command the script printed and ask
the user to run it themselves by typing
! <command>in the prompt; installs need sudo or an interactive prompt, so never run the install yourself. Once they say it is installed, run the checker again to confirm.
Missing LaTeX/poppler is a degraded mode, not a hard stop: the pipeline still runs but skips the compile and page-fit checks. Say so if the user chooses not to install.
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 · 24 lines · 62 tokens per session scan B b51d2cd858c9
setup is a skill published in the GitHub repository ledq/resumery (1 stars, last pushed 18d ago), licensed MIT. It adds 62 tokens to every session and 267 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
save-pdf-kb
Convert a local or public remote PDF into an auditable Markdown knowledge-base bundle with the original document, inferred headings, page provenance, OCR text, image metadata, and local visual assets. Use when the user asks to save, import, archive, extract, or turn a PDF into KB Markdown, especially scanned documents…
cv-claw
Use this skill when the user wants to ingest a resume or CV into structured JSON, tailor an existing resume for a specific job, tweak how a rendered resume looks, or design a new resume template — even if they don't explicitly say "resume," "CV," or "cv-claw." Covers parsing PDFs, images, screenshots, or pasted text…
markitdown
Converts heterogeneous documents and selected URIs to Markdown with Microsoft MarkItDown for text analysis, search, and LLM/RAG ingestion. Covers safe local conversion, streams, Office/PDF/data formats, batch workflows, plugins, vision OCR, Azure extraction, and the official MCP server.
pydicom
Reads, inspects, writes, transforms, and preflights local DICOM datasets and pixel data. Applies to DICOM metadata, transfer syntaxes, compression plugins, frames, private elements, JSON, and bounded de-identification review.
liteparse
Local document and PDF parsing that returns spatial text with bounding boxes. Use for extracting text from PDFs, DOCX, Office files, and images; running OCR on scans; producing layout-preserved JSON for RAG; batch-ingesting folders of papers; or rendering pages to PNG for multimodal agents. Distinguishing capabilities…
open-notebook
Organizes research with the self-hosted Open Notebook alternative to NotebookLM. Supports source ingestion (PDFs, web pages, audio, video, and Office documents), cited document chat, text and vector search, notes, custom transformations, and multi-speaker podcasts. Use when automating Open Notebook through its REST…