pdf

Extract text and tables from PDFs using open-source Python libraries.

Updated Feb 4, 2026
One-click install
npx skills add https://github.com/Rishabhupadhya/ai-content-repurpose --skill pdf-rishabhupadhya
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: pdf
Source: https://github.com/Rishabhupadhya/ai-content-repurpose/tree/main/.agents/skills/pdf
Command: npx skills add https://github.com/Rishabhupadhya/ai-content-repurpose --skill pdf-rishabhupadhya

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

PDF handling often requires multiple tools, manual steps, and inconsistent results when converting, merging, or extracting data from documents.

Core Features & Use Cases

  • Read, extract text and tables from PDFs; merge or split documents; rotate pages; apply watermarks; create new PDFs; encrypt/decrypt; extract images; OCR on scanned PDFs to make them searchable.
  • Real-world use: automate processing of batches of PDFs to extract structured data and metadata for archival or data-entry workflows.
  • Use case: convert a batch of invoices into a structured dataset for accounting and reporting.

Quick Start

Ask me to process a PDF file and specify the operation you want, such as extracting text from document.pdf.

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 PDF files for data processing?

Extract text and tables from PDF files using open-source Python libraries like pypdf and pdfplumber. The Skill processes documents to read, modify, and extract structured data from PDFs entirely through local environments without requiring paid APIs.

Can I run OCR on scanned PDFs to make them searchable without paid APIs?

Yes, you can run OCR on scanned PDFs to make them searchable without paid APIs. The Skill uses pytesseract and pdf2image to perform optical character recognition entirely on open-source models and tools in local environments.

How do I merge, split, and encrypt PDF documents in an automated workflow?

Merge, split, and encrypt PDF documents in an automated workflow using open-source Python libraries. The Skill handles merging, splitting, rotating, watermarking, and encryption/decryption to automate processing of batches of PDFs for archival or data-entry workflows.

Does this PDF processing approach work entirely on local open-source tools?

Yes, this PDF processing approach works entirely on local open-source tools. It operates without paid APIs and relies on open-source models and Python libraries including pypdf, pdfplumber, pdf2image, Pillow, and pytesseract for all document operations.

What's the best way to convert a batch of PDF invoices into a structured dataset?

The best way to convert a batch of PDF invoices into a structured dataset is automating extraction with this Skill. It processes batches of PDFs to extract structured data and metadata, making it suitable for accounting, reporting, and data-entry workflows.

Why use open-source Python libraries instead of paid APIs for PDF data extraction?

Use open-source Python libraries instead of paid APIs for PDF data extraction to avoid recurring costs and maintain local control. The Skill leverages pypdf and pdfplumber to read and extract data from documents without paid API dependencies.