/markitdown
Convert files and office documents to Markdown. Supports PDF, DOCX, PPTX, XLSX, images (with OCR), audio (with transcription), HTML, CSV, JSON, XML, ZIP, YouTube URLs, EPubs and more.
$ npx -y skills add foryourhealth111-pixel/Vibe-Skills --skill markitdown --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/markitdown
Context preview
The summary Claude sees to decide when to auto-load this skill.
Convert files and office documents to Markdown. Supports PDF, DOCX, PPTX, XLSX, images (with OCR), audio (with transcription), HTML, CSV, JSON, XML, ZIP, YouTube URLs, EPubs and more.
SKILL.md
markitdown.SKILL.mdname: markitdown
description: Convert files and office documents to Markdown. Supports PDF, DOCX, PPTX, XLSX, images (with OCR), audio (with transcription), HTML, CSV, JSON, XML, ZIP, YouTube URLs, EPubs and more.
allowed-tools: Read Write Edit Bash
license: MIT license
metadata:
skill-author: K-Dense Inc.MarkItDown - File to Markdown Conversion
Overview
MarkItDown is a Python tool developed by Microsoft for converting various file formats to Markdown. It's particularly useful for converting documents into LLM-friendly text format, as Markdown is token-efficient and well-understood by modern language models.
**Key Benefits**:
- Convert documents to clean, structured Markdown
- Token-efficient format for LLM processing
- Supports 15+ file formats
- Optional AI-enhanced image descriptions
- OCR for images and scanned documents
- Speech transcription for audio files
Visual Enhancement with Scientific Schematics
**When creating documents with this skill, always consider adding scientific diagrams and schematics to enhance visual communication.**
If your document does not already contain schematics or diagrams:
- Use the **scientific-schematics** skill to generate AI-powered publication-quality diagrams
- Simply describe your desired diagram in natural language
- Nano Banana Pro will automatically generate, review, and refine the schematic
**For new documents:** Scientific schematics should be generated by default to visually represent key concepts, workflows, architectures, or relationships described in the text.
**How to generate schematics:**
python scripts/generate_schematic.py "your diagram description" -o figures/output.png
The AI will automatically:
- Create publication-quality images with proper formatting
- Review and refine through multiple iterations
- Ensure accessibility (colorblind-friendly, high contrast)
- Save outputs in the figures/ directory
**When to add schematics:**
- Document conversion workflow diagrams
- File format architecture illustrations
- OCR processing pipeline diagrams
- Integration workflow visualizations
- System architecture diagrams
- Data flow diagrams
- Any complex concept that benefits from visualization
For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.
---
Supported Formats
| Format | Description | Notes | |--------|-------------|-------| | **PDF** | Portable Document Format | Full text extraction | | **DOCX** | Microsoft Word | Tables, formatting preserved | | **PPTX** | PowerPoint | Slides with notes | | **XLSX** | Excel spreadsheets | Tables and data | | **Images** | JPEG, PNG, GIF, WebP | EXIF metadata + OCR | | **Audio** | WAV, MP3 | Metadata + transcription | | **HTML** | Web pages | Clean conversion | | **CSV** | Comma-separated values | Table format | | **JSON** | JSON data | Structured representation | | **XML** | XML documents | Structured format | | **ZIP** | Archive files | Iterates contents | | **EPUB** | E-books | Full text extraction | | **YouTube** | Video URLs | Fetch transcriptions |
Quick Start
Installation
# Install with all features
pip install 'markitdown[all]'
# Or from source
git clone https://github.com/microsoft/markitdown.git
cd markitdown
pip install -e 'packages/markitdown[all]'
Command-Line Usage
# Basic conversion
markitdown document.pdf > output.md
# Specify output file
markitdown document.pdf -o output.md
# Pipe content
cat document.pdf | markitdown > output.md
# Enable plugins
markitdown --list-plugins # List available plugins
markitdown --use-plugins document.pdf -o output.md
Python API
from markitdown import MarkItDown
# Basic usage
md = MarkItDown()
result = md.convert("document.pdf")
print(result.text_content)
# Convert from stream
with open("document.pdf", "rb") as f:
result = md.convert_stream(f, file_extension=".pdf")
print(result.text_content)Advanced Features
1. AI-Enhanced Image Descriptions
Use LLMs via OpenRouter to generate detailed image descriptions (for PPTX and image files):
from markitdown import MarkItDown
from openai import OpenAI
# Initialize OpenRouter client (OpenAI-compatible API)
client = OpenAI(
api_key="your-openrouter-api-key",
base_url="https://openrouter.ai/api/v1"
)
md = MarkItDown(
llm_client=client,
llm_model="anthropic/claude-opus-4.5", # recommended for scientific vision
llm_prompt="Describe this image in detail for scientific documentation"
)
result = md.convert("presentation.pptx")
print(result.text_content)2. Azure Document Intelligence
For enhanced PDF conversion with Microsoft Document Intelligence:
# Command line
markitdown document.pdf -o output.md -d -e "<document_intelligence_endpoint>"
# Python API
from markitdown import MarkItDown
md = MarkItDown(docintel_endpoint="<document_intelligence_endpoint>")
result = md.convert("complex_document.pdf")
print(result.text_content)3. Plugin System
MarkItDown supports 3rd-party plugins for extending functionality:
# List installed plugins
markitdown --list-plugins
# Enable plugins
markitdown --use-plugins file.pdf -o output.md
Find plugins on GitHub with hashtag: `#markitdown-plugin`
Optional Dependencies
Control which file formats you support:
# Install specific formats
pip install 'markitdown[pdf, docx, pptx]'
# All available options:
# [all] - All optional dependencies
# [pptx] - PowerPoint files
# [docx] - Word documents
# [xlsx] - Excel spreadsheets
# [xls] - Older Excel files
# [pdf] - PDF documents
# [outlook] - Outlook messages
# [az-doc-intel] - Azure Document Intelligence
# [audio-transcription] - WAV and MP3 transcription
# [youtube-transcription] - YouTube video transcription
Common Use Cases
1. Con
Read more
name: markitdown
description: Convert files and office documents to Markdown. Supports PDF, DOCX, PPTX, XLSX, images (with OCR), audio (with transcription), HTML, CSV, JSON, XML, ZIP, YouTube URLs, EPubs and more.
allowed-tools: Read Write Edit Bash
license: MIT license
metadata:
skill-author: K-Dense Inc.MarkItDown - File to Markdown Conversion
Overview
MarkItDown is a Python tool developed by Microsoft for converting various file formats to Markdown. It's particularly useful for converting documents into LLM-friendly text format, as Markdown is token-efficient and well-understood by modern language models.
**Key Benefits**:
- Convert documents to clean, structured Markdown
- Token-efficient format for LLM processing
- Supports 15+ file formats
- Optional AI-enhanced image descriptions
- OCR for images and scanned documents
- Speech transcription for audio files
Visual Enhancement with Scientific Schematics
**When creating documents with this skill, always consider adding scientific diagrams and schematics to enhance visual communication.**
If your document does not already contain schematics or diagrams:
- Use the **scientific-schematics** skill to generate AI-powered publication-quality diagrams
- Simply describe your desired diagram in natural language
- Nano Banana Pro will automatically generate, review, and refine the schematic
**For new documents:** Scientific schematics should be generated by default to visually represent key concepts, workflows, architectures, or relationships described in the text.
**How to generate schematics:**
python scripts/generate_schematic.py "your diagram description" -o figures/output.png
The AI will automatically:
- Create publication-quality images with proper formatting
- Review and refine through multiple iterations
- Ensure accessibility (colorblind-friendly, high contrast)
- Save outputs in the figures/ directory
**When to add schematics:**
- Document conversion workflow diagrams
- File format architecture illustrations
- OCR processing pipeline diagrams
- Integration workflow visualizations
- System architecture diagrams
- Data flow diagrams
- Any complex concept that benefits from visualization
For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.
---
Supported Formats
| Format | Description | Notes | |--------|-------------|-------| | **PDF** | Portable Document Format | Full text extraction | | **DOCX** | Microsoft Word | Tables, formatting preserved | | **PPTX** | PowerPoint | Slides with notes | | **XLSX** | Excel spreadsheets | Tables and data | | **Images** | JPEG, PNG, GIF, WebP | EXIF metadata + OCR | | **Audio** | WAV, MP3 | Metadata + transcription | | **HTML** | Web pages | Clean conversion | | **CSV** | Comma-separated values | Table format | | **JSON** | JSON data | Structured representation | | **XML** | XML documents | Structured format | | **ZIP** | Archive files | Iterates contents | | **EPUB** | E-books | Full text extraction | | **YouTube** | Video URLs | Fetch transcriptions |
Quick Start
Installation
# Install with all features pip install 'markitdown[all]' # Or from source git clone https://github.com/microsoft/markitdown.git cd markitdown pip install -e 'packages/markitdown[all]'
Command-Line Usage
# Basic conversion markitdown document.pdf > output.md # Specify output file markitdown document.pdf -o output.md # Pipe content cat document.pdf | markitdown > output.md # Enable plugins markitdown --list-plugins # List available plugins markitdown --use-plugins document.pdf -o output.md
Python API
from markitdown import MarkItDown
# Basic usage
md = MarkItDown()
result = md.convert("document.pdf")
print(result.text_content)
# Convert from stream
with open("document.pdf", "rb") as f:
result = md.convert_stream(f, file_extension=".pdf")
print(result.text_content)Advanced Features
1. AI-Enhanced Image Descriptions
Use LLMs via OpenRouter to generate detailed image descriptions (for PPTX and image files):
from markitdown import MarkItDown
from openai import OpenAI
# Initialize OpenRouter client (OpenAI-compatible API)
client = OpenAI(
api_key="your-openrouter-api-key",
base_url="https://openrouter.ai/api/v1"
)
md = MarkItDown(
llm_client=client,
llm_model="anthropic/claude-opus-4.5", # recommended for scientific vision
llm_prompt="Describe this image in detail for scientific documentation"
)
result = md.convert("presentation.pptx")
print(result.text_content)2. Azure Document Intelligence
For enhanced PDF conversion with Microsoft Document Intelligence:
# Command line markitdown document.pdf -o output.md -d -e "<document_intelligence_endpoint>"
# Python API
from markitdown import MarkItDown
md = MarkItDown(docintel_endpoint="<document_intelligence_endpoint>")
result = md.convert("complex_document.pdf")
print(result.text_content)3. Plugin System
MarkItDown supports 3rd-party plugins for extending functionality:
# List installed plugins markitdown --list-plugins # Enable plugins markitdown --use-plugins file.pdf -o output.md
Find plugins on GitHub with hashtag: `#markitdown-plugin`
Optional Dependencies
Control which file formats you support:
# Install specific formats pip install 'markitdown[pdf, docx, pptx]' # All available options: # [all] - All optional dependencies # [pptx] - PowerPoint files # [docx] - Word documents # [xlsx] - Excel spreadsheets # [xls] - Older Excel files # [pdf] - PDF documents # [outlook] - Outlook messages # [az-doc-intel] - Azure Document Intelligence # [audio-transcription] - WAV and MP3 transcription # [youtube-transcription] - YouTube video transcription
Common Use Cases
1. Con
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