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Extract text and tables from PDFs using Python libraries.

3|Updated Feb 5, 2026
Search Tags:#ocr#pdf#split#merge#forms#text-extraction#table-extraction
One-click install
npx skills add https://github.com/nano-step/skill-manager --skill pdf-nano-step
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: pdf
Source: https://github.com/nano-step/skill-manager/tree/main/skills/pdf
Command: npx skills add https://github.com/nano-step/skill-manager --skill pdf-nano-step

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

PDFs often contain unstructured text and tables that are difficult to extract, reuse, and integrate into downstream workflows.

Core Features & Use Cases

  • Text and table extraction from PDFs
  • Merge, split, rotate, and watermark PDFs
  • Fill forms and apply password protection
  • Use cases include processing invoices, archiving reports, and digitizing forms for automation.

Quick Start

Use a simple, natural-language command to extract data from a PDF and generate a structured output.

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 a PDF for downstream workflows?▼

PDF extraction automates pulling unstructured text and tables into reusable data. Using Python libraries like pdfplumber, you can parse invoices and reports to generate structured outputs for downstream automation workflows.

What is the best way to merge and split PDF documents using Python?▼

Merging and splitting PDFs is best handled code-driven with Python libraries like pypdf. This approach ensures reproducible document archiving and processing, allowing you to automate combining multiple files or separating pages based on specific criteria.

Can I fill PDF forms and apply password protection programmatically?▼

Yes, you can fill PDF forms and apply password protection programmatically. This digitizes administrative workflows by automating form completion and securing documents through reproducible, Python-based processing.

Does this PDF processing approach support OCR for digitizing scanned documents?▼

OCR support for digitizing scanned PDF documents is included. This allows you to extract text from image-based forms and reports, converting otherwise unstructured content into editable, searchable data for archiving and automation.

What Python libraries are needed for code-driven PDF generation and processing?▼

Python-based tooling for PDF processing requires libraries like pypdf, pdfplumber, and reportlab. These dependencies enable reproducible code-driven workflows for tasks ranging from text extraction to generating new report documents.

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