paper-analysis

To analyze an arXiv PDF paper and extract methods, formulas, and experimental results, provide the Skill with an arXiv ID, paper URL, or local file path. It uses a map-reduce process to break the PDF into pages and synthesize structured, evidence-backed explanations.

Yes, you can extract tables and figures from research PDFs without a vision model. The Skill provides separate workflows for vision-enabled and text-only environments, relying on PyMuPDF and pypdf for reliable page extraction and multimodal analysis.

The best way to generate a literature review from an academic research paper is to input the PDF into the Skill. It extracts concrete metrics, baselines, prior work, and limitations, synthesizing them into a coherent long-form report.

Yes, this paper analysis tool works with local PDF files and OpenAI-compatible APIs. It requires PyMuPDF, pypdf, Pillow, and OpenAI API support to handle PDF intake and multimodal page analysis.

PDF page extraction fails during experimental analysis when reliable PDF acquisition is interrupted or dependencies like PyMuPDF and pypdf encounter complex formatting. The Skill requires these specific libraries to properly parse dense academic papers.

The limitation of using map-reduce for academic research paper analysis is that breaking a paper into individual pages can sometimes fragment context. However, the Skill synthesizes these page-level findings into a coherent, evidence-backed report.