A professional-grade document processing skill that enables AI agents to read, parse, and extract key information from PDF, Word, and PowerPoint files.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install document-pro
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 document-pro using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Document Pro is a comprehensive extension designed for AI agents within the Openclaw Skills ecosystem. It provides the technical bridge needed to transform unstructured document formats—such as PDF, DOCX, PPTX, and XLSX—into structured, actionable intelligence. By leveraging industry-standard libraries, this skill allows agents to not just see text, but to understand the structure and hierarchy of complex files.
Whether you are building a research assistant or a business automation bot, Document Pro ensures your agent can handle everything from academic papers to corporate spreadsheets. It is a vital component for developers who want to integrate deep document understanding into their Openclaw Skills projects, enabling high-fidelity data extraction and content synthesis.
To integrate Document Pro into your environment, you must install the necessary processing libraries. Use the following command to set up the dependencies for these Openclaw Skills:
pip install pdfplumber PyPDF2 python-docx python-pptx openpyxl
Ensure your agent has the appropriate file system permissions to read and write to your document directories.
Document Pro handles various file taxonomies as detailed below:
| Format | Read Support | Write Support | Underlying Tools |
|---|---|---|---|
| Yes | Yes | pdfplumber, PyPDF2 | |
| DOCX | Yes | Yes | python-docx |
| PPTX | Yes | No | python-pptx |
| XLSX | Yes | Yes | openpyxl |
| TXT/MD | Yes | Yes | Built-in |
Every processing task returns a metadata object containing the document type, page/slide count, and a structured summary array.
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