How does it handle complex mathematical equations?

The skill detects multi-line equations and automatically wraps them in math code blocks to prevent GitHub's markdown pre-processor from stripping backslashes, ensuring formulas render correctly.

Why does it distinguish between Word-generated and LaTeX PDFs?

Word-generated PDFs often encode math as Unicode text which traditional OCR tools fail to extract correctly; this skill detects the source type to suggest the most accurate conversion path.

Does this skill work for GitLab users?

Yes, it includes specific logic for GitLab's Comrak parser, noting where GitHub-specific workarounds are unnecessary and warning about GitLab.com's 50-span rendering limit.

Can it extract images and figures from the PDF?

Yes, it includes a Python-based extraction script that identifies figures within PDF pages and saves them to a media directory with standardized naming for easy Markdown referencing.

What software dependencies are required?

The skill utilizes tools like pymupdf4llm, uv for Python environment management, and KaTeX for math validation.

Academic PDF to GitHub Markdown Converter

Name: Academic PDF to GitHub Markdown Converter
Author: terrylica

byterrylica

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Aprendizaje y Documentación

Converts complex research papers and technical PDFs into clean, GitHub-renderable Markdown with accurate LaTeX math and extracted figures.

This skill provides a specialized workflow for transforming academic PDFs into GitHub Flavored Markdown (GFM). It solves the common problem of garbled math equations on GitHub by intelligently selecting between standard LaTeX delimiters and code blocks based on specific rendering engine quirks. It includes logic for detecting PDF source types (Word-generated, LaTeX, or scanned), automated image extraction, and KaTeX validation to ensure documentation remains professional and readable across version control platforms like GitHub and GitLab.

Características Principales

01Cross-platform compatibility mapping for rendering math on both GitHub.com and self-hosted GitLab instances.

02Automated figure and image extraction with size-based noise filtering to exclude icons and watermarks.

03Source-aware PDF analysis to determine optimal extraction methods for Word, LaTeX, or scanned sources.

04Integrated validation pipeline using KaTeX to verify mathematical syntax before pushing to a repository.

0540 GitHub stars

06Advanced LaTeX formatting logic that prevents GitHub's markdown pre-processor from breaking multiline equations.

Casos de Uso

01Migrating math-heavy legacy documentation from PDF format to a version-controlled Markdown environment.

02Converting arXiv papers or technical reports for documentation sites hosted on GitHub Pages or Wikis.

03Building a searchable, collaborative knowledge base of research papers within a Git repository.

Características Principales

01Cross-platform compatibility mapping for rendering math on both GitHub.com and self-hosted GitLab instances.

02Automated figure and image extraction with size-based noise filtering to exclude icons and watermarks.

03Source-aware PDF analysis to determine optimal extraction methods for Word, LaTeX, or scanned sources.

04Integrated validation pipeline using KaTeX to verify mathematical syntax before pushing to a repository.

0540 GitHub stars

06Advanced LaTeX formatting logic that prevents GitHub's markdown pre-processor from breaking multiline equations.

Casos de Uso

01Migrating math-heavy legacy documentation from PDF format to a version-controlled Markdown environment.

02Converting arXiv papers or technical reports for documentation sites hosted on GitHub Pages or Wikis.

03Building a searchable, collaborative knowledge base of research papers within a Git repository.