pdf

Extract text, tables, and images from PDF documents.

2|Updated Jun 4, 2026
One-click install
npx skills add https://github.com/Lord1Egypt/scientific-agent-toolkit --skill pdf-lord1egypt
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: pdf
Source: https://github.com/Lord1Egypt/scientific-agent-toolkit/tree/main/scientific-skills/pdf
Command: npx skills add https://github.com/Lord1Egypt/scientific-agent-toolkit --skill pdf-lord1egypt

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pypdf, pdfplumber, reportlab, pdf2image, pytesseract, pypdfium2, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This skill solves the challenge of interacting with PDF documents, which are notoriously difficult to manipulate, fill, or extract data from programmatically.

Core Features & Use Cases

  • Advanced Form Automation: Handles both native fillable fields and non-fillable documents via coordinate-based annotation.
  • Data Extraction: Provides robust tools for pulling text, tables, and images from complex PDF layouts.
  • Use Case: Use this to batch-process hundreds of scanned invoices, extract specific table data into Excel, or programmatically fill out standardized government or corporate forms.

Quick Start

Use the pdf skill to extract all text and tables from the document named report.pdf and save the results to a new file.

Frequently Asked Questions about pdf

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I extract text and tables from complex PDF layouts?

To extract text and tables from PDF layouts, you can use this skill to pull structured content from documents. It leverages libraries like pdfplumber to parse complex layouts and save the extracted data to new files for analysis.

Can I automate PDF form filling for documents without native fillable fields?

Yes, you can automate PDF form filling for non-fillable documents using coordinate-based text annotation. This skill supports both native form fields and coordinate-based annotation to programmatically populate standardized forms.

What is the best way to process scanned PDFs and extract data from images?

The best way to process scanned PDFs and extract data is by using OCR. This skill uses pytesseract and pdf2image to perform OCR on scanned documents, converting image-based text into machine-readable data for extraction.

Does this PDF data extraction approach require specific Python libraries?

Yes, this PDF data extraction approach requires Python-based libraries including pypdf, pdfplumber, reportlab, and pytesseract. These dependencies provide the document analysis and modification capabilities needed for complex workflows.

How do I batch process hundreds of scanned invoices for data extraction?

You can batch process hundreds of scanned invoices by using this skill to automate data extraction. It supports complex workflows to pull specific table data from multiple PDF files and export the results for further use.

What are the limitations of using pypdf for document processing?

While pypdf handles basic text extraction, limitations arise with complex layouts and scanned documents. This skill overcomes these limitations by integrating pdfplumber for tables and pytesseract for OCR on image-based PDFs.