paper-analyzer

PDF parsing for academic papers requires the MinerU Cloud API to accurately extract text, images, tables, and formulas, alongside Python libraries to handle the subsequent Markdown and HTML generation from the extracted content.

You extract formulas and tables from a research paper PDF by submitting the file to the MinerU Cloud API, which isolates these elements during parsing and allows the Skill to generate optional detailed formula explanations within the final HTML or Markdown article.

Yes, you can generate a storytelling style article from an academic paper by specifying the desired writing format during processing, transforming dense research text into an engaging blog post suitable for a wider audience.

Yes, the PDF to Markdown conversion supports optional GitHub code analysis, allowing you to analyze associated code repositories alongside the extracted text and formula explanations when generating the final technical article.

The best way to create a concise summary from an academic PDF is to use a parsing tool that extracts structural elements like formulas and tables, then apply a concise writing style template to generate a brief Markdown overview.