content-parser

To generate structured study notes from a PDF, upload your file to generate a five-dimension Markdown template including a reading guide, breakdown, slang, culture, and transformation. This process automatically extracts long sentences and cultural context specifically for TOEFL prep.

Yes, you can extract slang and cultural context from academic articles. The parser breaks down complex texts and links cultural context to TOEFL-style learning, outputting a GitHub-ready Markdown template with dedicated sections for slang and cultural analysis.

Yes, the parser supports MD materials alongside PDFs using pypdf for text extraction. It applies deterministic parsing to generate your five-dimension notes, automatically falling back to pdftotext if needed to ensure successful extraction.

The best way to parse long sentences into flashcards is to upload your PDF for automatic extraction. The Skill breaks down complex texts and outputs a structured GitHub-ready Markdown template that can be directly used for study notes and flashcards.

You do not need to manage Python directly to parse PDFs and MDs into reading guides. The Skill handles the Python-based text extraction internally using pypdf, allowing you to simply upload your document and receive the structured Markdown output.

A limitation of using pypdf for academic article text extraction is potential formatting loss, which the Skill addresses by falling back to pdftotext. It focuses on extracting textual context, slang, and long sentences rather than preserving visual layouts.