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Markitdown

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jimmc414
markitdown

Convert various file formats (PDF, Office documents, images, audio, web content, structured data) to Markdown optimized for LLM processing. Use when converting documents to markdown, extracting text from PDFs/Office files, transcribing audio, performing OCR on images, extracting YouTube transcripts, or processing batches of files. Supports 20+ formats including DOCX, XLSX, PPTX, PDF, HTML, EPUB, CSV, JSON, images with OCR, and audio with transcription.

Overview

Publisherjimmc414
RepositoryKosmos
Skill namemarkitdown
Stars
585
Forks
105
Bundled files
6
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by jimmc414 on GitHub. Read the source before you install it.

Installation

Install the Markitdown AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/jimmc414/Kosmos.git /tmp/Kosmos
mkdir -p .claude/skills
cp -r /tmp/Kosmos/kosmos-claude-scientific-skills/scientific-skills/markitdown .claude/skills/markitdown
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Markitdown in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Markitdown on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Markitdown is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

MarkItDown

Overview

MarkItDown is a Python utility that converts various file formats into Markdown format, optimized for use with large language models and text analysis pipelines. It preserves document structure (headings, lists, tables, hyperlinks) while producing clean, token-efficient Markdown output.

When to Use This Skill

Use this skill when users request:

  • Converting documents to Markdown format
  • Extracting text from PDF, Word, PowerPoint, or Excel files
  • Performing OCR on images to extract text
  • Transcribing audio files to text
  • Extracting YouTube video transcripts
  • Processing HTML, EPUB, or web content to Markdown
  • Converting structured data (CSV, JSON, XML) to readable Markdown
  • Batch converting multiple files or ZIP archives
  • Preparing documents for LLM analysis or RAG systems

Core Capabilities

1. Document Conversion

Convert Office documents and PDFs to Markdown while preserving structure.

Supported formats:

  • PDF files (with optional Azure Document Intelligence integration)
  • Word documents (DOCX)
  • PowerPoint presentations (PPTX)
  • Excel spreadsheets (XLSX, XLS)

Basic usage:

python
from markitdown import MarkItDown

md = MarkItDown()
result = md.convert("document.pdf")
print(result.text_content)

Command-line:

bash
markitdown document.pdf -o output.md

See references/document_conversion.md for detailed documentation on document-specific features.

2. Media Processing

Extract text from images using OCR and transcribe audio files to text.

Supported formats:

  • Images (JPEG, PNG, GIF, etc.) with EXIF metadata extraction
  • Audio files with speech transcription (requires speech_recognition)

Image with OCR:

python
from markitdown import MarkItDown

md = MarkItDown()
result = md.convert("image.jpg")
print(result.text_content)  # Includes EXIF metadata and OCR text

Audio transcription:

python
result = md.convert("audio.wav")
print(result.text_content)  # Transcribed speech

See references/media_processing.md for advanced media handling options.

3. Web Content Extraction

Convert web-based content and e-books to Markdown.

Supported formats:

  • HTML files and web pages
  • YouTube video transcripts (via URL)
  • EPUB books
  • RSS feeds

YouTube transcript:

python
from markitdown import MarkItDown

md = MarkItDown()
result = md.convert("https://youtube.com/watch?v=VIDEO_ID")
print(result.text_content)

See references/web_content.md for web extraction details.

4. Structured Data Handling

Convert structured data formats to readable Markdown tables.

Supported formats:

  • CSV files
  • JSON files
  • XML files

CSV to Markdown table:

python
from markitdown import MarkItDown

md = MarkItDown()
result = md.convert("data.csv")
print(result.text_content)  # Formatted as Markdown table

See references/structured_data.md for format-specific options.

5. Advanced Integrations

Enhance conversion quality with AI-powered features.

Azure Document Intelligence: For enhanced PDF processing with better table extraction and layout analysis:

python
from markitdown import MarkItDown

md = MarkItDown(docintel_endpoint="<endpoint>", docintel_key="<key>")
result = md.convert("complex.pdf")

LLM-Powered Image Descriptions: Generate detailed image descriptions using GPT-4o:

python
from markitdown import MarkItDown
from openai import OpenAI

client = OpenAI()
md = MarkItDown(llm_client=client, llm_model="gpt-4o")
result = md.convert("presentation.pptx")  # Images described with LLM

See references/advanced_integrations.md for integration details.

6. Batch Processing

Process multiple files or entire ZIP archives at once.

ZIP file processing:

python
from markitdown import MarkItDown

md = MarkItDown()
result = md.convert("archive.zip")
print(result.text_content)  # All files converted and concatenated

Batch script: Use the provided batch processing script for directory conversion:

bash
python scripts/batch_convert.py /path/to/documents /path/to/output

See scripts/batch_convert.py for implementation details.

Installation

Full installation (all features):

bash
uv pip install 'markitdown[all]'

Modular installation (specific features):

bash
uv pip install 'markitdown[pdf]'           # PDF support
uv pip install 'markitdown[docx]'          # Word support
uv pip install 'markitdown[pptx]'          # PowerPoint support
uv pip install 'markitdown[xlsx]'          # Excel support
uv pip install 'markitdown[audio]'         # Audio transcription
uv pip install 'markitdown[youtube]'       # YouTube transcripts

Requirements:

  • Python 3.10 or higher

Output Format

MarkItDown produces clean, token-efficient Markdown optimized for LLM consumption:

  • Preserves headings, lists, and tables
  • Maintains hyperlinks and formatting
  • Includes metadata where relevant (EXIF, document properties)
  • No temporary files created (streaming approach)

Common Workflows

Preparing documents for RAG:

python
from markitdown import MarkItDown

md = MarkItDown()

# Convert knowledge base documents
docs = ["manual.pdf", "guide.docx", "faq.html"]
markdown_content = []

for doc in docs:
    result = md.convert(doc)
    markdown_content.append(result.text_content)

# Now ready for embedding and indexing

Document analysis pipeline:

bash
# Convert all PDFs in directory
for file in documents/*.pdf; do
    markitdown "$file" -o "markdown/$(basename "$file" .pdf).md"
done

Plugin System

MarkItDown supports extensible plugins for custom conversion logic. Plugins are disabled by default for security:

python
from markitdown import MarkItDown

# Enable plugins if needed
md = MarkItDown(enable_plugins=True)

Resources

This skill includes comprehensive reference documentation for each capability:

  • references/document_conversion.md - Detailed PDF, DOCX, PPTX, XLSX conversion options
  • references/media_processing.md - Image OCR and audio transcription details
  • references/web_content.md - HTML, YouTube, and EPUB extraction
  • references/structured_data.md - CSV, JSON, XML conversion formats
  • references/advanced_integrations.md - Azure Document Intelligence and LLM integration
  • scripts/batch_convert.py - Batch processing utility for directories

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Markitdown AI skill do?

Convert various file formats (PDF, Office documents, images, audio, web content, structured data) to Markdown optimized for LLM processing. Use when converting documents to markdown, extracting text from PDFs/Office files, transcribing audio, performing OCR on images, extracting YouTube transcripts, or processing batches of files. Supports 20+ formats including DOCX, XLSX, PPTX, PDF, HTML, EPUB, CSV, JSON, images with OCR, and audio with transcription.

Why use Markitdown on TypingMind?

Because you install it once and use it with any model. Markitdown is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Markitdown in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jimmc414/Kosmos/tree/master/kosmos-claude-scientific-skills/scientific-skills/markitdown. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Markitdown?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Markitdown?

As many as you like. As long as a model supports skills, you can use Markitdown with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Markitdown AI skill free?

It is published on GitHub by jimmc414. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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