A comprehensive suite for programmatically managing PDF documents through text extraction, table parsing, and advanced document generation.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install latex-formula-extraction-pdf
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 latex-formula-extraction-pdf 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 Manipulation Toolkit is a robust set of tools designed for developers who need to handle PDF documents at scale. This Openclaw Skills integration provides a bridge between AI agents and complex PDF operations, including layout-aware text extraction, structured table parsing, and programmatic PDF creation. By leveraging industry-standard libraries like pypdf, pdfplumber, and reportlab, it enables seamless automation of document workflows.
Whether you are processing high volumes of invoices, generating dynamic reports, or managing secure, password-protected documents, this skill provides the necessary technical depth. It supports both high-level Python scripting and efficient command-line utilities, ensuring that users of Openclaw Skills can choose the most effective tool for their specific document processing needs.
To get started with these Openclaw Skills, ensure you have the necessary Python libraries and system utilities installed:
# Install Python dependencies
pip install pypdf pdfplumber reportlab pandas pytesseract pdf2image
# Install system CLI tools (Debian/Ubuntu)
sudo apt-get install poppler-utils qpdf pdftk
The toolkit interacts with PDF files and generates structured data outputs as described below:
| Data Type | format | Description |
|---|---|---|
| Metadata | JSON/Dict | Contains Title, Author, Subject, and Creator fields. |
| Tables | List of Lists | Extracted rows and columns suitable for Pandas DataFrames. |
| Text Content | String | Plain text or layout-preserved text extracted from pages. |
| Images | JPG/PNG | Embedded assets extracted from PDF pages via poppler-utils. |
| Document Info | Object | Page counts, dimensions, and rotation properties. |
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