microsoft/cat-agent-skills is a static website that catalogs reusable instruction sets and related packages for AI agents. People use it to search, filter, rate, and download skills for Cowork, Copilot Studio, and Scout, along with Copilot plugins and Scout automations. The catalogue entries are the skills, instructions, plugins, and settings displayed by the site.
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 microsoft/cat-agent-skills --skill doc-format-convertergit clone --depth 1 https://github.com/microsoft/cat-agent-skillsWrote 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/microsoft/cat-agent-skills/doc-format-converter)<a href="https://agentmods.dev/skills/microsoft/cat-agent-skills/doc-format-converter"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/doc-format-converter/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/microsoft/cat-agent-skills/doc-format-converter"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/doc-format-converter.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00131 | $0.01183 |
| Opus 5 | $0.00066 | $0.00592 |
| Sonnet 5 | $0.00026 | $0.00237 |
| Haiku 4.5 | $0.00013 | $0.00118 |
Grade A, and why
doc-format-converter 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 9d 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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Convert documents between formats using the bundled scripts/convert.py. It
works fully offline with libraries already present in the sandbox
(markitdown, mammoth, markdownify, reportlab, python-docx, python-pptx,
pdfplumber, beautifulsoup4, magika) and routes each conversion through the
highest-fidelity pipeline available.
Division of labor with the analyzing-* skills
This skill produces files; the built-in analyzing-* skills answer
questions. Route accordingly:
- "What does this PDF say?", "find X in this workbook", "summarize this
deck" → use
analyzing-pdf/analyzing-xlsx/analyzing-pptxetc., not this skill. In particular, never useconvert.pyas a substitute extraction path for PDF question-answering —analyzing-pdfowns that. - "Give me this as a PDF/Word doc/slides/markdown file" → this skill.
- If the user asks content questions after a conversion, hand off to the
matching
analyzing-*skill on the original file rather than answering from this skill's intermediate output. - Reuse their artifacts when present. If an
analyzing-*preprocessor has already produced aconverted.mdfor the source file, feed that toconvert.pyas Markdown input (convert.py converted.md --to pptx) instead of re-extracting the original — it is a high-quality extraction with page markers and pipe tables.
Instructions
-
Identify the input file and the target format the user wants. Targets:
md,html,pdf,docx,pptx,txt. Inputs additionally includexlsxandcsv. -
Run the converter by the script's path inside this skill's folder — typically
/app/skills/doc-format-converter/— so it works regardless of the current working directory:python /app/skills/doc-format-converter/scripts/convert.py INPUT --to FORMAT [-o OUTPUT]It prints the output path on success. If
-ois omitted, the output lands next to the input with the new extension. -
For a folder of files, use batch mode and share the printed summary table with the user:
What ships with it
11 files 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.
- assets/samples/sample.csv 76 B
- assets/samples/sample.docx 36 KB
- assets/samples/sample.html 993 B
- assets/samples/sample.md 945 B
- assets/samples/sample.pptx 30 KB
- assets/samples/sample.xlsx 4.9 KB
- metadata.json 509 B
- references/test-cases.md 5.7 KB
- scripts/blocks.py 8.3 KB runs code
- scripts/convert.py 13 KB runs code
- scripts/render.py 14 KB runs code
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.
- 9d ago First seen · 98 lines · 131 tokens per session scan A fcb552a84ac5
doc-format-converter is a skill published in the GitHub repository microsoft/cat-agent-skills (64 stars, last pushed yesterday), licensed MIT. It adds 131 tokens to every session and 1,183 once invoked, about $0.0007 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 2026-08-30.
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