# MarkItDown Skill - Creation Summary ## Overview A comprehensive skill for using Microsoft's MarkItDown tool has been created for the Claude Scientific Writer. This skill enables conversion of 15+ file formats to Markdown, optimized for LLM processing and scientific workflows. ## What Was Created ### Core Documentation 1. **SKILL.md** (Main skill file) - Complete guide to MarkItDown - Quick start examples - All supported formats - Advanced features (AI, Azure DI) - Best practices - Use cases and examples 2. **README.md** - Skill overview - Key features - Quick reference - Integration guide 3. **QUICK_REFERENCE.md** - Cheat sheet for common tasks - Quick syntax reference - Common commands - Troubleshooting tips 4. **INSTALLATION_GUIDE.md** - Step-by-step installation - System dependencies - Virtual environment setup - Optional features - Troubleshooting ### Reference Documentation Located in `references/`: 1. **api_reference.md** - Complete API documentation - Class and method references - Custom converter development - Plugin system - Error handling - Breaking changes guide 2. **file_formats.md** - Detailed format-specific guides - 15+ supported formats - Format capabilities and limitations - Best practices per format - Example outputs ### Utility Scripts Located in `scripts/`: 1. **batch_convert.py** - Parallel batch conversion - Multi-format support - Recursive directory search - Progress tracking - Error reporting - Command-line interface 2. **convert_with_ai.py** - AI-enhanced conversions - Predefined prompt types (scientific, medical, data viz, etc.) - Custom prompt support - Multiple model support - OpenRouter integration (Claude Sonnet 4.5 default) 3. **convert_literature.py** - Scientific literature conversion - Metadata extraction from filenames - Year-based organization - Automatic index generation - JSON catalog creation - Front matter support ### Assets Located in `assets/`: 1. **example_usage.md** - 20+ practical examples - Basic conversions - Scientific workflows - AI-enhanced processing - Batch operations - Error handling patterns - Integration examples ### License - **LICENSE.txt** - MIT License from Microsoft ## Skill Structure ``` .claude/skills/markitdown/ ├── SKILL.md # Main skill documentation ├── README.md # Skill overview ├── QUICK_REFERENCE.md # Quick reference guide ├── INSTALLATION_GUIDE.md # Installation instructions ├── SKILL_SUMMARY.md # This file ├── LICENSE.txt # MIT License ├── references/ │ ├── api_reference.md # Complete API docs │ └── file_formats.md # Format-specific guides ├── scripts/ │ ├── batch_convert.py # Batch conversion utility │ ├── convert_with_ai.py # AI-enhanced conversion │ └── convert_literature.py # Literature conversion └── assets/ └── example_usage.md # Practical examples ``` ## Capabilities ### File Format Support - **Documents**: PDF, DOCX, PPTX, XLSX, XLS, EPUB - **Images**: JPEG, PNG, GIF, WebP (with OCR) - **Audio**: WAV, MP3 (with transcription) - **Web**: HTML, YouTube URLs - **Data**: CSV, JSON, XML - **Archives**: ZIP files - **Email**: Outlook MSG files ### Advanced Features 1. **AI Enhancement via OpenRouter** - Access to 100+ AI models through OpenRouter - Multiple preset prompts (scientific, medical, data viz) - Custom prompt support - Default: Claude Sonnet 4.5 (best for scientific vision) - Choose best model for each task 2. **Azure Integration** - Azure Document Intelligence for complex PDFs - Enhanced layout understanding - Better table extraction 3. **Batch Processing** - Parallel conversion with configurable workers - Recursive directory processing - Progress tracking and error reporting - Format-specific organization 4. **Scientific Workflows** - Literature conversion with metadata - Automatic index generation - Year-based organization - Citation-friendly output ## Integration with Scientific Writer The skill has been added to the Scientific Writer's skill catalog: - **Location**: `.claude/skills/markitdown/` - **Skill Number**: #5 in Document Manipulation Skills - **SKILLS.md**: Updated with complete skill description ### Usage Examples ``` > Convert all PDFs in the literature folder to Markdown > Convert this PowerPoint presentation to Markdown with AI-generated descriptions > Extract tables from this Excel file > Transcribe this lecture recording ``` ## Scripts Usage ### Batch Convert ```bash python scripts/batch_convert.py input_dir/ output_dir/ --extensions .pdf .docx --workers 4 ``` ### AI-Enhanced Convert ```bash export OPENROUTER_API_KEY="sk-or-v1-..." python scripts/convert_with_ai.py paper.pdf output.md \ --model anthropic/claude-sonnet-4.5 \ --prompt-type scientific ``` ### Literature Convert ```bash python scripts/convert_literature.py papers/ markdown/ --organize-by-year --create-index ``` ## Key Features 1. **Token-Efficient Output**: Markdown optimized for LLM processing 2. **Comprehensive Format Support**: 15+ file types 3. **AI Enhancement**: Detailed image descriptions via OpenAI 4. **OCR Support**: Extract text from scanned documents 5. **Audio Transcription**: Speech-to-text for audio files 6. **YouTube Support**: Video transcript extraction 7. **Plugin System**: Extensible architecture 8. **Batch Processing**: Efficient parallel conversion 9. **Error Handling**: Robust error management 10. **Scientific Focus**: Optimized for research workflows ## Installation ```bash # Full installation pip install 'markitdown[all]' # Selective installation pip install 'markitdown[pdf,docx,pptx,xlsx]' ``` ## Quick Start ```python from markitdown import MarkItDown # Basic usage md = MarkItDown() result = md.convert("document.pdf") print(result.text_content) # With AI via OpenRouter from openai import OpenAI client = OpenAI( api_key="your-openrouter-api-key", base_url="https://openrouter.ai/api/v1" ) md = MarkItDown( llm_client=client, llm_model="anthropic/claude-sonnet-4.5" # or openai/gpt-4o ) result = md.convert("presentation.pptx") ``` ## Documentation Files | File | Purpose | Lines | |------|---------|-------| | SKILL.md | Main documentation | 400+ | | api_reference.md | API documentation | 500+ | | file_formats.md | Format guides | 600+ | | example_usage.md | Practical examples | 500+ | | batch_convert.py | Batch conversion | 200+ | | convert_with_ai.py | AI conversion | 200+ | | convert_literature.py | Literature conversion | 250+ | | QUICK_REFERENCE.md | Quick reference | 300+ | | INSTALLATION_GUIDE.md | Installation guide | 300+ | **Total**: ~3,000+ lines of documentation and code ## Use Cases 1. **Literature Review**: Convert research papers to Markdown for analysis 2. **Data Extraction**: Extract tables from Excel/PDF for processing 3. **Presentation Processing**: Convert slides with AI descriptions 4. **Document Analysis**: Prepare documents for LLM consumption 5. **Lecture Transcription**: Convert audio recordings to text 6. **YouTube Analysis**: Extract video transcripts 7. **Archive Processing**: Batch convert document collections ## Next Steps 1. Install MarkItDown: `pip install 'markitdown[all]'` 2. Read `QUICK_REFERENCE.md` for common tasks 3. Try example scripts in `scripts/` directory 4. Explore `SKILL.md` for comprehensive guide 5. Check `example_usage.md` for practical examples ## Resources - **MarkItDown GitHub**: https://github.com/microsoft/markitdown - **PyPI**: https://pypi.org/project/markitdown/ - **OpenRouter**: https://openrouter.ai (AI model access) - **OpenRouter API Keys**: https://openrouter.ai/keys - **OpenRouter Models**: https://openrouter.ai/models - **License**: MIT (Microsoft Corporation) - **Python**: 3.10+ required - **Skill Location**: `.claude/skills/markitdown/` ## Success Criteria ✅ Comprehensive skill documentation created ✅ Complete API reference provided ✅ Format-specific guides included ✅ Utility scripts implemented ✅ Practical examples documented ✅ Installation guide created ✅ Quick reference guide added ✅ Integration with Scientific Writer complete ✅ SKILLS.md updated ✅ Scripts made executable ✅ MIT License included ## Skill Status **Status**: ✅ Complete and Ready to Use The MarkItDown skill is fully integrated into the Claude Scientific Writer and ready for use. All documentation, scripts, and examples are in place.