pdf-explore

Navigate PDFs and extract structured content using pypdfium2 and Python.

288|34|Updated Jul 6, 2026

Search Tags:#pdf #analysis #scientific research #document navigation #structured data extraction

Ready to run

npx skills add https://github.com/PKU-YuanGroup/OpenAI4S --skill pdf-explore-pku-yuangroup

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: pdf-explore
Source: https://github.com/PKU-YuanGroup/OpenAI4S/tree/main/skills/pdf-explore
Command: npx skills add https://github.com/PKU-YuanGroup/OpenAI4S --skill pdf-explore-pku-yuangroup

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pypdfium2, pillow, qpdf, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a robust solution for navigating through complex PDF documents and extracting valuable information with ease.

Core Features & Use Cases

PDF Navigation: Efficiently navigate through large PDFs by summarizing sections, finding relevant pages, and using table of contents.
Content Extraction: Extract and analyze structured data from PDFs, such as figures, citations, and table rows.
Use Case: When analyzing a scientific paper, this Skill can quickly summarize the methods section, find the pages discussing specific topics, and extract figure captions.

Quick Start

To explore a PDF, use the 'pdf-explore' skill with 'pdf_pages' or 'pdf_scan' to find relevant content or 'pdf_extract' for structured data extraction.

Frequently Asked Questions about pdf-explore

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

FAQPage Schema

How do I extract structured data like figures and citations from a PDF?▼

To extract structured data like figures and citations from a PDF, use the pdf_extract functionality. It analyzes and pulls specific structured elements such as figure captions, citations, and table rows for research and administrative workflows.

What is the best way to navigate large PDF documents and summarize specific sections?▼

The best way to navigate large PDF documents and summarize specific sections is by using the pdf_scan or pdf_pages features. These tools efficiently locate relevant pages, summarize sections, and utilize the table of contents for precise navigation.

How does PDF content extraction work with pypdfium2 and pillow?▼

PDF content extraction with pypdfium2 and pillow works by utilizing Python for text parsing and image handling. The system operates with pypdfium2 to render PDF pages and relies on qpdf for robust parsing and navigation tasks.

Can I use Python to find relevant pages discussing specific topics in scientific research papers?▼

Yes, you can use Python to find relevant pages discussing specific topics in scientific research papers. The system scans PDFs, summarizes sections like methods, and identifies exact pages covering your targeted research topics.

Do I need qpdf and pypdfium2 installed to parse PDFs and extract text?▼

Yes, you need qpdf, pypdfium2, and pillow installed to parse PDFs and extract text. These dependencies are required for the underlying PDF rendering, text parsing, and image handling operations.

What are the limitations when using Python for PDF document navigation?▼

Limitations when using Python for PDF document navigation depend on the pypdfium2 and qpdf parsing capabilities. Complex layouts or scanned images without text layers may restrict text extraction and structured data analysis accuracy.