PDF OCR Extraction

What This Skill Does

The PDF OCR Extraction skill is a powerful tool for OpenClaw users designed to convert static, image-based documents into machine-readable text. Whether you are dealing with scanned invoices, physical contracts, archived books, or images of receipts, this skill utilizes advanced Optical Character Recognition (OCR) to identify characters and layout structures. It bridges the gap between raw visual data and actionable digital information, allowing you to search, copy, and analyze the contents of files that were previously locked within a static image format. The skill supports various output formats, including plain text, structured Markdown tables, and even the creation of fully searchable PDF files that maintain the original visual integrity of the document.

Installation

To add this capability to your OpenClaw agent, use the following command in your terminal or command-line interface:

clawhub install openclaw/skills/skills/lijie420461340/pdf-ocr

Once installed, the skill integrates directly with your agent's document processing workflow. Ensure you have the necessary file permissions for your agent to read your source PDFs from your local file system or cloud storage integration.

Use Cases

• Digitizing Paperwork: Convert physical scanned documents into editable digital archives.
• Data Entry Automation: Extract data from tables in PDF reports and convert them into structured JSON or Markdown formats for spreadsheet imports.
• Searchable Archiving: Turn batches of legacy PDFs into text-searchable files, drastically improving document discovery and management.
• Historical Analysis: Process scanned books or archives where text formatting is complex and requires layout preservation.

Example Prompts

1. "Please OCR the invoice scanned on my desktop and extract the date, total amount, and vendor name into a table."
2. "Take the document titled 'research_paper_scan.pdf' and generate a searchable PDF version while maintaining the original image layout."
3. "Extract all text from pages 5 through 12 of the provided document and highlight any words with low confidence levels."

Tips & Limitations

For the best results, ensure your input files are scanned at a minimum of 300 DPI. Documents with poor contrast, extreme skew, or heavy shadows may result in lower confidence scores. While typed text achieves high accuracy (95%+), handwritten content—especially cursive—is significantly less reliable. If you notice persistent errors, consider pre-processing your images to improve brightness and alignment before running the skill. Always review the 'Uncertain Text' report generated by the skill if the overall confidence score is below 85%.