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figureya-pdf-parser

Extracts figures from PDFs and generates corresponding FigureYa modules.

Updated Apr 17, 2026
Search Tags:#academic research#PDF#module generation#figure extraction#FigureYa
One-click install
npx skills add https://github.com/ying-ge/FigureYa-skills --skill figureya-pdf-parser
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: figureya-pdf-parser
Source: https://github.com/ying-ge/FigureYa-skills/tree/main/skills/figureya-pdf-parser
Command: npx skills add https://github.com/ying-ge/FigureYa-skills --skill figureya-pdf-parser

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pymupdf, claudesight, textblob, sklearn, numpy, matplotlib, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates the extraction of figures from PDFs and generates corresponding FigureYa modules, streamlining the process of working with scientific and medical visualizations.

Core Features & Use Cases

  • PDF Figure Extraction: Extract all images and full text from PDF documents using PDF parsing, text mining, and AI vision recognition.
  • Module Generation: Generate FigureYa modules based on extracted figures using AI-powered code generation.
  • Automation Modes: Supports fully automatic, semi-automatic, and assisted modes for flexible use.
  • Use Case: Automate the process of extracting figures from research papers and generating publication-ready FigureYa visualizations.

Quick Start

Run the figureya-pdf-parser skill with the command: figureya-pdf-parser --input input.pdf

Frequently Asked Questions about figureya-pdf-parser

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

FAQPage Schema
How do I extract figures from a PDF for academic research?▼

To extract figures from a PDF for academic research, this Skill automates the process using PDF parsing and AI vision recognition. It identifies and pulls all images and full text from scientific documents to streamline visualization workflows.

What is the best way to generate visualization modules from extracted PDF images?▼

The best way to generate visualization modules from extracted PDF images is using an automated AI-powered code generation approach. This Skill creates FigureYa modules directly from extracted figures, producing publication-ready visualizations for scientific papers.

Does PDF figure extraction work with PyMuPDF and AI vision capabilities?▼

Yes, PDF figure extraction works with PyMuPDF and AI vision capabilities. This Skill requires PyMuPDF for parsing PDF documents and leverages Claude's AI vision for accurate figure recognition, supplemented by Python libraries like textblob and sklearn.

Can I automate figure processing for scientific publications in different modes?▼

Yes, you can automate figure processing for scientific publications in fully automatic, semi-automatic, and assisted modes. This flexibility allows you to handle varying levels of extraction complexity and generate corresponding modules based on your specific needs.

Why do I need Python libraries like numpy and matplotlib for PDF figure extraction?▼

You need Python libraries like numpy and matplotlib for PDF figure extraction to handle additional data processing and visualization tasks. These dependencies support the underlying text mining, image manipulation, and generation of publication-ready outputs.

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