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 julianobarbosa/claude-code-skills --skill markitdowngit clone --depth 1 https://github.com/julianobarbosa/claude-code-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/julianobarbosa/claude-code-skills/markitdown)<a href="https://agentmods.dev/skills/julianobarbosa/claude-code-skills/markitdown"><img src="https://agentmods.dev/badge/skills/julianobarbosa/claude-code-skills/markitdown.svg" alt="Measured on agentmods" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 254 Docker image references without a specific tag (:latest is implicit) or digest (@sha256:...) can be silently replaced by a malicious image.Fix: Pin the image: image:tag or image@sha256:abc123
- low MCP Rug Pull · line 235 pip install without ==version installs the latest release, which could include malicious changes.Fix: Pin the version: pip install package==1.2.3
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 | $0.00084 | $0.01953 |
| Opus 5 | $0.00042 | $0.00977 |
| Sonnet 5 | $0.00017 | $0.00391 |
| Haiku 4.5 | $0.00008 | $0.00195 |
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 8d 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 — 311 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MarkItDown Skill
Microsoft's Python utility for converting various file formats to Markdown for LLM and text analysis pipelines.
Overview
MarkItDown converts documents while preserving structure (headings, lists, tables, links). It's optimized for LLM consumption rather than human-readable output.
Supported Formats
| Category | Formats |
|---|---|
| Documents | PDF, Word (DOCX), PowerPoint (PPTX), Excel (XLSX, XLS) |
| Media | Images (EXIF + OCR), Audio (WAV, MP3 transcription) |
| Web | HTML, YouTube URLs, Wikipedia, RSS/Atom feeds |
| Data | CSV, JSON, XML, Jupyter notebooks (.ipynb) |
| Archives | ZIP (iterates contents), EPub |
| Outlook MSG files |
Quick Start
Installation
# Full installation (recommended)
pip install 'markitdown[all]'
# Minimal with specific formats
pip install 'markitdown[pdf,docx,pptx]'
# Using uv
uv pip install 'markitdown[all]'
Optional Dependencies
| Extra | Description |
|---|---|
[all] |
All optional dependencies |
[pdf] |
PDF file support |
[docx] |
Word documents |
[pptx] |
PowerPoint presentations |
[xlsx] |
Excel spreadsheets |
[xls] |
Legacy Excel files |
[outlook] |
Outlook MSG files |
[az-doc-intel] |
Azure Document Intelligence |
[audio-transcription] |
WAV/MP3 transcription |
[youtube-transcription] |
YouTube video transcripts |
Command-Line Usage
# Basic conversion
markitdown document.pdf > output.md
# Specify output file
markitdown document.pdf -o output.md
# Pipe input
cat document.pdf | markitdown > output.md
# With Azure Document Intelligence
markitdown document.pdf -o output.md -d -e "<endpoint>"
Python API
from markitdown import MarkItDown
# Basic conversion
md = MarkItDown()
result = md.convert("document.xlsx")
print(result.text_content)
# With LLM for image descriptions
from openai import OpenAI
client = OpenAI()
md = MarkItDown(
llm_client=client,
llm_model="gpt-4o",
llm_prompt="Describe this image in detail"
)
result = md.convert("image.jpg")
print(result.text_content)
# With Azure Document Intelligence
md = MarkItDown(docintel_endpoint="<your-endpoint>")
result = md.convert("complex-document.pdf")
print(result.text_content)
What ships with it
7 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.
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.
- 8d ago First seen · 311 lines · 84 tokens per session scan A 8d010ef074c0
markitdown is a skill published in the GitHub repository julianobarbosa/claude-code-skills (10 stars, last pushed 12d ago), licensed MIT. It adds 84 tokens to every session and 1,953 once invoked, about $0.0004 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 2026-08-31.
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