A high-performance document conversion tool that leverages Microsoft's MarkItDown library to turn various file formats into structured Markdown.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install markitdown-converter
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install markitdown-converter using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The MarkItDown Document Converter is a specialized tool designed to bridge the gap between static document formats and structured text. By utilizing this Openclaw Skills extension, developers can automate the conversion of PDF, Word, PowerPoint, and Excel files into Markdown format. This is particularly useful for AI-driven workflows where clean, text-based data is required for RAG (Retrieval-Augmented Generation), analysis, or long-term storage in documentation repositories.
To get started with this skill, ensure you have Python 3.10 or higher installed. You can install the required library using the following commands:
# Install the MarkItDown library with all extras
python3.12 -m pip install --user --break-system-packages "markitdown[all]"
For advanced PDF processing and OCR support, install these system dependencies:
# macOS users
brew install poppler tesseract
# Linux users
sudo apt install poppler-utils tesseract-ocr
Verify your installation with:
python3.12 -c "from markitdown import MarkItDown; print('Installation Successful!')"
The skill organizes its output to ensure compatibility with modern documentation tools. The data organization is as follows:
| Component | Description | File Format |
|---|---|---|
| Markdown Text | The primary converted content with preserved headers and lists | .md |
| Asset Folder | Directory containing extracted images from the source file | /images |
| Tables | Complex data structures converted to Markdown table syntax | Inline |
| OCR Metadata | Extracted text from scanned images and non-selectable PDFs | Inline |
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