---
name: markitdown-cbebc1873aa6
description: 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.
---

# 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
pip install 'markitdown[all]'
```

**Modular installation (specific features):**
```bash
pip install 'markitdown[pdf]'           # PDF support
pip install 'markitdown[docx]'          # Word support
pip install 'markitdown[pptx]'          # PowerPoint support
pip install 'markitdown[xlsx]'          # Excel support
pip install 'markitdown[audio]'         # Audio transcription
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


---
Source attribution: ljchg12-hue
Original project: https://github.com/ljchg12-hue/dotfiles/blob/aa5001cbf018bedcfc28fc67a2f119df062f838b/skills/scientific-skills/scientific-packages/markitdown/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2025 K-Dense Inc.

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.


# Mega AI Hub resource metadata

Creator / publisher: ljchg12-hue
Original project: https://github.com/ljchg12-hue/dotfiles/blob/aa5001cbf018bedcfc28fc67a2f119df062f838b/skills/scientific-skills/scientific-packages/markitdown/SKILL.md
Attribution basis: Source repository record

Fields of work: Marketing
Roles: Content Marketer, Growth Marketer, Marketing Analyst, Product Marketer, SEO Specialist
Specialties: API
Tools: Azure Document Intelligence, Speech_Recognition
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 844e4f7f22782d445a15d3d520f08896e93f059d1c058555c7d47cb8d5d8d555