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 skills add dcassil/resume-kit --skill export-resumegit clone --depth 1 https://github.com/dcassil/resume-kitWrote 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/dcassil/resume-kit/export-resume)<a href="https://agentmods.dev/skills/dcassil/resume-kit/export-resume"><img src="https://agentmods.dev/badge/skills/dcassil/resume-kit/export-resume/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/dcassil/resume-kit/export-resume"><img src="https://agentmods.dev/badge/skills/dcassil/resume-kit/export-resume.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 | $0.00058 | $0.01367 |
| Opus 5.5 | $0.00023 | $0.00547 |
| Sonnet 5.5 | $0.00012 | $0.00273 |
| Haiku 4.5 | $0.00006 | $0.00137 |
Grade A, and why
export-resume 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Inputs must be canonical JSON. This capability consumes a resume as a
ResumeDocumentJSON (build it from a PDF/DOCX/MD/text file with the parse-resume skill) and, where a job is involved, aJobDescriptionJSON (build it with parse-job so skills-coverage scoring works). Run those conversions in subagents, then pass the saved JSON paths here — they live underresume-kit/resumes/andresume-kit/jobs/.
Prerequisites
Run the shared Prerequisites gate first — see
_shared/prerequisites.md.
- Required input: a
ResumeDocumentJSON (config.jsonactive_resume, aresume-kit/working/<session>/resume.json, or an explicit path). - If missing: STOP and run parse-resume to produce the
ResumeDocumentJSON before exporting.
Purpose
Render a ResumeDocument to bytes and persist them through an ArtifactStore.
The response data field carries an ArtifactRef (also present in artifacts)
that the caller uses to retrieve the rendered bytes — raw bytes are never
embedded directly in the envelope. The artifact id is deterministic: callers
may supply an explicit artifact_id; otherwise it is derived from a SHA-256
hash of the format plus the rendered content (no UUIDs, timestamps, or random
values).
When to use
- When the user wants a finished, downloadable resume file (PDF or DOCX).
- After
update-keywords,update-terminology, or any editing step, to produce the final artifact. - When a downstream system requires a binary file rather than a JSON document.
Inputs
| Field | Type | Notes |
|---|---|---|
resume |
ResumeDocument |
The resume to render |
format |
"pdf" | "docx" |
Output format |
options |
ExportOptions | null |
Optional render options (see below) |
artifact_id |
str | null |
Optional explicit artifact id; omit for deterministic hash |
ExportOptions (all fields optional; defaults shown)
| Option | Default | Effect |
|---|---|---|
font_family |
"Helvetica" |
Base font family name |
font_size_pt |
11 |
Body font size in points |
margin_mm |
20.0 |
Page margin in millimetres (all sides) |
include_hyperlinks |
true |
Render URLs as clickable hyperlinks when supported |
page_size |
"letter" |
Page size identifier: "letter" or "a4" |
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 · 125 lines · 58 tokens per session scan A 6fb5c6c064a3
export-resume is a skill published in the GitHub repository dcassil/resume-kit (0 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 58 tokens to every session and 1,367 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.
Other skills, from other repositories
apify-youtube-transcript-scraper
Get YouTube captions, timestamped quotations, SRT/VTT and translated transcripts for videos, channels and playlists through the harshmaur/youtube-transcript-scraper Apify Actor.
foundry-hosted-agent-validation
Step-by-step process for validating a Python Foundry hosted agent sample (under python/samples/04-hosting/foundry-hosted-agents/) end to end — running it locally (native runtime and azd ai agent run) and after deploying it to an Azure AI Foundry project with azd. Use this when asked to validate a hosted agent sample.
skill-doc-delivery
Convert markdown to DOCX, PPTX, XLSX, PDF office documents — use when you need exportable deliverables.
meta-web-to-pdf-briefing
Render a topic into a distributable PDF briefing in three steps: web search → bullet summary → styled PDF. Trigger when the user asks for a PDF briefing on a single topic.
chat-complex-documents
Chat with and search your complex documents — ask questions, extract tables and fields, and get answers grounded in the source. Connects the hosted Unstructured Transform MCP server to parse, structure, and enrich PDFs, Word/Excel/PowerPoint, images, scanned files, emails, and 60+ other formats into clean, AI-ready…
pkf-writing
Author, update, convert, validate, persist, and render PKF (.pkf) content through message-inline, Library Asset, or Memory Page carriers. Use for structured reports, knowledge pages, delivery cards, or any .pkf body. NOT for recall, memory-graph placement, or curation decisions — those belong to the memory skill.