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 skills/team-commonly/commonly/markdown-converternpx skills add Team-Commonly/commonly --skill markdown-convertergit clone --depth 1 https://github.com/Team-Commonly/commonlyWhat 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 | $0.00057 | $0.00565 |
| Opus 5 | $0.00028 | $0.00282 |
| Sonnet 5 | $0.00011 | $0.00113 |
| Haiku 4.5 | $0.00006 | $0.00056 |
Grade A, and why
markdown-converter scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
markdown-converter — binary doc → markdown for agent input
markitdown is installed via pip3 install markitdown and is on PATH. It
extracts text content from a wide range of binary formats and emits clean
markdown that's efficient for LLM context.
Supported input formats
PDF, DOCX, XLSX, PPTX, HTML, EPUB, images (with OCR), CSV, JSON, audio transcripts, ZIP archives.
Basic usage
# Convert a single file to markdown on stdout
markitdown /workspace/$(basename "$PWD")/input.pdf
# Save to a markdown file
markitdown /workspace/$(basename "$PWD")/input.docx > /workspace/$(basename "$PWD")/input.md
# Convert and pipe directly into another tool
markitdown /workspace/$(basename "$PWD")/spec.xlsx | head -200
Reading a user-attached file
Files attached by users are downloaded to the agent workspace by the gateway. Once you have a workspace path:
# 1. Convert the binary to markdown
markitdown /workspace/$(basename "$PWD")/uploads/report.pdf > /tmp/report.md
# 2. Read the markdown into your context
cat /tmp/report.md
Then summarize, answer questions about it, or feed sections back to the user.
Useful flags
| Flag | Effect |
|---|---|
--use-docintel <ENDPOINT> |
Use Azure Doc Intelligence (requires API key) for OCR-heavy PDFs |
-o <file> |
Write to file instead of stdout |
When NOT to use markdown-converter
- For producing documents (md → DOCX/PDF/XLSX) → use
officecliorpandic-officeinstead. - For PDF manipulation (extract specific pages, merge files) → use the
pdfskill.
Troubleshooting
- OCR-heavy scanned PDF returns garbage — markitdown uses basic text extraction. If the PDF is image-only, the result will be empty or unhelpful. Mention this limitation to the user.
- XLSX with charts — markitdown extracts cell data but ignores embedded
charts. For chart inspection, render the workbook to HTML first via
officecli view <file> html.
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.
- 2d ago First seen · 67 lines · 57 tokens per session scan A 8b080e2ca0a3
markdown-converter is a skill published in the GitHub repository Team-Commonly/commonly (1,323 stars, last pushed 3d ago), licensed Apache-2.0. It adds 57 tokens to every session and 565 once invoked, about $0.0003 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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