PDF Processor Skill for Openclaw

A comprehensive suite for AI agents to automate PDF extraction, conversion, OCR, and security operations.

pengsc1994
v1.0.0
Apr 27, 2026
0
1.5k
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install free-pdf-processor

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install free-pdf-processor using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).

Prefer to download?

Get the raw skill files in a ZIP archive.

What is PDF Processor Skill?

The PDF Processor is a versatile toolkit designed to bridge the gap between static documents and actionable data within an AI-driven environment. As a key component of Openclaw Skills, it provides developers and AI agents with the ability to programmatically manipulate PDF files, performing everything from high-fidelity text and table extraction to complex format transformations. Whether you are dealing with digital-first documents or scanned images requiring OCR, this skill provides a robust layer of automation.

By integrating this tool, users can transform unstructured PDF data into structured formats like Excel or Word, making it an essential utility for data analysts and developers alike. It leverages powerful Python libraries to ensure that even complex layouts and encrypted files are handled with precision, maintaining the integrity of the original content while providing the flexibility needed for modern Openclaw Skills workflows.

PDF Processor Skill Use Cases

  • Automating the extraction of tabular data from financial reports for direct export to Excel.
  • Converting bulk PDF archives into editable Word documents for content repurposing.
  • Applying company watermarks and AES-256 encryption to sensitive legal documents automatically.
  • Using OCR to digitize scanned invoices and extract searchable text for database entry.
  • Merging multiple report fragments into a single cohesive document or splitting large files into individual pages.

How PDF Processor Skill Works

  1. The AI agent identifies the specific document task requested, such as extraction, conversion, or modification.
  2. The Openclaw Skills runner invokes the relevant Python script (e.g., extract_tables.py or pdf_to_word.py) with the specified input file path.
  3. The skill utilizes specialized engines like PyMuPDF for layout analysis or Tesseract for optical character recognition.
  4. The document is processed according to the defined parameters, such as compression levels or specific metadata extraction.
  5. The resulting file or data payload is saved to the output directory, and a success confirmation or data summary is returned to the user.

PDF Processor Skill Setup

To get started with this Openclaw Skills package, navigate to the skill directory and install the necessary Python dependencies:

cd pdf-processor
pip install pymupdf pdfplumber python-docx openpyxl pillow pytesseract

For OCR functionality, ensure Tesseract OCR is installed on your host system. On macOS, use brew install tesseract; on Linux, use sudo apt install tesseract-ocr; for Windows, download the installer from the official GitHub wiki.

PDF Processor Skill Data Schema & Taxonomy

The PDF Processor organizes its operations through a clear input/output structure and metadata tracking:

Component Details
Supported Inputs Standard PDF files, scanned image PDFs, and directories for batching
Extraction Outputs Plain text (.txt), structured Excel (.xlsx), and images (.png)
Document Outputs Editable Word (.docx), merged/split/compressed PDFs
Metadata Taxonomy Captures Title, Author, Creator, and Creation Date when available
Security Supports user and owner passwords for AES-256 encryption

PDF Processor Skill Advanced Features

  • Batch processing mode to execute operations on hundreds of files in a single command via batch_process.py.
  • Customizable OCR with support for multi-language recognition and layout preservation.
  • Five selectable compression levels to balance file size reduction against image quality.
  • Advanced table detection that handles merged cells and complex borderless grid structures.
  • Integrated metadata management to extract or strip document properties for privacy.

SKILL.md


Loading

Related Openclaw Skills

METADATA

Github Stars: 0
forks: 0

Featured*