Claude Scientific Writer is an AI-assisted research and writing tool that searches literature and produces documents such as scientific papers, reports, posters, grant proposals, and reviews with citations. Researchers and technical writers can use it as a Claude Code plugin, Python package, or command-line tool, with the catalogue entries defining agent workflows for it.
Borrowing it
Nothing to install: this file belongs to K-Dense-AI/claude-scientific-writer. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/K-Dense-AI/claude-scientific-writer/main/.claude/skills/markitdown/SKILL.mdgit clone --depth 1 https://github.com/K-Dense-AI/claude-scientific-writerWrote 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/k-dense-ai/claude-scientific-writer/markitdown)<a href="https://agentmods.dev/skills/k-dense-ai/claude-scientific-writer/markitdown"><img src="https://agentmods.dev/badge/skills/k-dense-ai/claude-scientific-writer/markitdown/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/k-dense-ai/claude-scientific-writer/markitdown"><img src="https://agentmods.dev/badge/skills/k-dense-ai/claude-scientific-writer/markitdown.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 | $0.00061 | $0.02487 |
| Opus 5 | $0.00030 | $0.01243 |
| Sonnet 5 | $0.00012 | $0.00497 |
| Haiku 4.5 | $0.00006 | $0.00249 |
Grade A, and why
markitdown 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 12d 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.
This is a copy
89% identical to markitdown — 19 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 265 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MarkItDown
Overview
MarkItDown is Microsoft's lightweight Python utility for turning common documents into structure-preserving Markdown. Its output is designed primarily for indexing, text analysis, search, and LLM ingestion—not high-fidelity visual reproduction.
This skill targets MarkItDown 0.1.6, released May 26, 2026. New code should use result.markdown; result.text_content remains only as a soft-deprecated compatibility alias.
Choose the Right Path
| Need | Recommended path |
|---|---|
| Trusted local PDF, Office, HTML, CSV, EPUB, or ZIP | Built-in converter with convert_local() |
| Uploaded bytes or an already-open file | convert_stream() with StreamInfo hints |
| Remote HTTP(S) input | Validate and fetch it yourself, then call convert_response() |
| Scanned PDF or text inside embedded images | Official markitdown-ocr vision plugin, Azure Document Intelligence, or Azure Content Understanding |
| Video, structured fields, or custom multimodal extraction | Azure Content Understanding |
| Local agent integration | Official markitdown-mcp server over STDIO or localhost |
| Bounding boxes, page coordinates, or screenshots | Use a layout-aware parser such as LiteParse instead |
| PDF merge/split/forms/watermarks | Use the pdf skill instead |
Installation
Create an isolated environment:
uv venv --python 3.12 .venv
source .venv/bin/activate
Install every built-in feature:
uv pip install "markitdown[all]==0.1.6"
Or install only the converters required by the task:
uv pip install "markitdown[pdf,docx,pptx,xlsx]==0.1.6"
Available extras in 0.1.6 are:
pptx,docx,xlsx,xls,pdf, andoutlookaudio-transcriptionandyoutube-transcriptionaz-doc-intelandaz-content-understandingall
Verify the installation:
markitdown --version
python scripts/inspect_installation.py
The [all] extra does not install the separate markitdown-ocr plugin or an OpenAI-compatible client.
What ships with it
10 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.
- references/api_reference.md 11 KB
- references/cloud_and_ocr.md 9.5 KB
- references/file_formats.md 10 KB
- references/mcp_and_plugins.md 6.5 KB
- references/migration.md 8.1 KB
- references/security.md 9.8 KB
- references/workflows.md 8.0 KB
- scripts/batch_convert.py 10 KB runs code
- scripts/convert_literature.py 12 KB runs code
- scripts/inspect_installation.py 4.8 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.
- 12d ago First seen · 265 lines · 61 tokens per session scan A ca8be4f687a1
markitdown is a skill published in the GitHub repository K-Dense-AI/claude-scientific-writer (2,327 stars, last pushed 24d ago), licensed MIT. It adds 61 tokens to every session and 2,487 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to markitdown, differing in 19 lines, and is treated as a copy.
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