A comprehensive document processing engine for creating, editing, merging, and extracting structured data from PDF files using Python-based tools.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install pdf-skill
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 pdf-skill using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The PDF skill is a robust solution for developers needing to programmatically handle complex document workflows within Openclaw Skills. It leverages industry-standard libraries like pypdf, pdfplumber, and weasyprint to provide a full suite of capabilities including text and table extraction, form filling, and metadata management.
Beyond basic manipulation, this Openclaw Skills extension supports advanced requirements such as OCR for scanned documents via Tesseract and professional-grade PDF generation from HTML/CSS templates. Whether you are automating invoice processing or generating dynamic monthly reports, this skill provides the necessary hooks and API references to streamline your document automation pipeline.
To get started with this skill, install the primary dependencies:
pip install pypdf pdfplumber weasyprint
For advanced features like OCR and image conversion, install the optional system requirements:
# For image conversion
brew install poppler
pip install pdf2image
# For OCR
brew install tesseract
pip install pytesseract
The PDF skill organizes metadata and extracted content into structured formats for easy integration with other Openclaw Skills.
| Data Type | format | Description |
|---|---|---|
| Metadata | Dictionary | Contains Title, Author, Subject, Creator, and Creation Date. |
| Extracted Text | String/JSON | Clean text content mapped by page number. |
| Tables | List of Lists | Raw table data extracted via pdfplumber, compatible with Pandas DataFrames. |
| Form Data | Key-Value Pair | Dictionary of field names and their corresponding string values. |
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