literature-reader

To extract text and tables from academic PDFs, the Skill applies pdfplumber as a reliable fallback to capture structured content. It then generates structured Markdown literature notes complete with metadata, methods, and explicit citations to specific sections and tables.

The best way to summarize methodology and results is by analyzing the PDF to extract metadata, evaluate experimental methods, and synthesize key findings. This generates a structured Markdown summary with explicit citations and a quality verification checklist.

Yes, you can generate a cross-paper comparison table for a batch literature review. The Skill processes multiple academic PDFs simultaneously to produce a horizontal comparison table that synthesizes metadata, methods, and results across all analyzed papers.

Yes, pdfplumber supports reliable Chinese and English PDF text extraction with specific page-range handling. The Skill uses this dependency as a fallback when built-in readers fail, ensuring accurate metadata and method analysis for multi-language academic papers.

When built-in PDF readers fail to extract academic content, use the provided Python script powered by pdfplumber. This fallback mechanism reliably extracts text and tables, enabling the continuous generation of structured Markdown literature notes.