pdf-explore

Parse, summarize, and search PDF documents with parallel processing.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/guanxiaol/open-science --skill pdf-explore
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: pdf-explore
Source: https://github.com/guanxiaol/open-science/tree/main/runtime/skills/pdf-explore
Command: npx skills add https://github.com/guanxiaol/open-science --skill pdf-explore

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pypdfium2, pillow, pypdf, and includes scripts (resource) and assets (resource) components.

What problem does it solve?

This Skill streamlines the process of analyzing and extracting information from large PDF documents, reducing the time and effort required for manual analysis.

Core Features & Use Cases

  • PDF Parsing: Extracts text and images from PDFs, including scanned documents.
  • Page Summarization: Provides a summary of the content of each page in a PDF.
  • Semantic Search: Enables searching for specific content within a PDF based on keywords.
  • Use Case: Suppose you have a lengthy scientific paper and need to quickly find information about a specific method or dataset. This Skill can help you locate and extract the relevant pages from the PDF, saving you time compared to reading the entire document.

Quick Start

Use the pdf-explore skill to extract a summary of each page from the attached file 'scientific_paper.pdf'.

Frequently Asked Questions about pdf-explore

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

FAQPage Schema
How do I extract specific information from a lengthy scientific paper PDF?

Parallel processing parses PDF documents to extract text and images, enabling semantic search for specific keywords. This quickly locates and extracts relevant pages from lengthy scientific papers without reading the entire document manually.

Can I get a summary of each page in a PDF document?

Yes, you can generate a summary of each page in a PDF document. The Skill parses the document using parallel processing and provides a summary of the content of each page, streamlining the review of academic research and legal analysis materials.

Does this PDF parsing approach work with scanned documents?

Yes, this Skill extracts text and images from scanned PDF documents. It utilizes the pypdfium2, pypdf, and pillow libraries to process and parse scanned files for information extraction and document review.

What's the best way to search for specific content within a large PDF?

The best way to search for specific content within a large PDF is using semantic search based on keywords. The Skill utilizes parallel processing to parse and search within the document, enabling you to quickly locate relevant information for legal analysis or academic research.

Do I need pypdfium2 and pillow to parse PDFs for academic research?

Yes, you need pypdfium2, pillow, and pypdf installed to parse PDFs for academic research. These libraries are required dependencies for the Skill to process documents, extract images, and perform parallel page summarization and semantic search.

Are there limitations when using parallel processing for PDF information extraction?

Limitations of parallel processing for PDF information extraction depend on the pypdfium2, pillow, and pypdf libraries handling your document. While it accelerates parsing and semantic search, users should ensure their system resources support concurrent processing of large academic research documents.