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ocr-and-documents

Extract text from PDFs and scanned documents via OCR and local extractors.

1|Updated Apr 12, 2026
Search Tags:#ocr#pdf#pymupdf#document-processing#text-extraction#web_extract
One-click install
npx skills add https://github.com/cryptopafi/nexusos-skills --skill ocr-and-documents-cryptopafi
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ocr-and-documents
Source: https://github.com/cryptopafi/nexusos-skills/tree/main/productivity/ocr-and-documents
Command: npx skills add https://github.com/cryptopafi/nexusos-skills --skill ocr-and-documents-cryptopafi

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires marker-pdf, pymupdf, pymupdf4llm, and includes scripts (resource) components.

What problem does it solve?

Extract text from PDFs and scanned documents and convert image-based content into readable, editable text and structured data for analysis, archiving, or reuse in other workflows.

Core Features & Use Cases

  • Remote URL extraction using web_extract to convert online PDFs quickly without local dependencies.
  • Local text extraction from PDFs with pymupdf for fast, lightweight processing of text-based documents.
  • OCR-based extraction with marker-pdf for scanned documents and complex layouts, including multilingual support.
  • Optional DOCX/PPTX guidance for parsing Word and slide decks via dedicated tools when needed.

Quick Start

Extract the text from document.pdf (or a URL) using web_extract first, with fallback to local extractors as needed.

Frequently Asked Questions about ocr-and-documents

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

FAQPage Schema
How do I extract text from scanned PDF documents?▼

Extracting text from scanned PDFs is handled by marker-pdf for OCR processing, which converts image-based pages into readable, structured text outputs. It handles complex layouts and multilingual content for academic papers and archival materials.

What is the best way to extract text from a local text-based PDF?▼

The best way to extract text from local text-based PDFs is using pymupdf for fast, lightweight processing. It directly reads embedded text without OCR, quickly converting documents like reports into structured outputs for analysis.

Can I extract text from PDFs hosted at a remote URL?▼

Yes, you can extract text from remote URLs using web_extract, which fetches and converts online PDFs quickly without local dependencies. It serves as the primary extraction method with fallback to local extractors like pymupdf as needed.

Does this PDF text extraction approach support DOCX and PPTX files?▼

Yes, this Skill provides optional DOCX and PPTX handling guidance. It recommends using dedicated tools like python-docx for Word files and python-pptx for slide decks to parse and extract text content from these formats.

When should I use OCR instead of local text extraction for PDFs?▼

You should use OCR via marker-pdf instead of local pymupdf extraction when processing scanned documents or image-based pages with complex layouts. Local extraction suits text-based PDFs, while OCR handles image content and multilingual support.

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