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SKILL.md
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:
from markitdown import MarkItDown
md = MarkItDown()
result = md.convert("document.pdf")
print(result.text_content)
Command-line:
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:
from markitdown import MarkItDown
md = MarkItDown()
result = md.convert("image.jpg")
print(result.text_content) # Includes EXIF metadata and OCR text
Audio transcription:
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:
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:
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:
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:
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:
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:
See scripts/batch_convert.py for implementation details.
Installation
Full installation (all features):
uv pip install 'markitdown[all]'
Modular installation (specific features):
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:
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:
# 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:
from markitdown import MarkItDown
# Enable plugins if needed
md = MarkItDown(enable_plugins=True)
Resources
This skill includes comprehensive reference documentation for each capability:
