What problem does it solve? Reading long books and retaining their content is time-consuming, and manually organizing chapter notes, quotes, and takeaways into a reusable knowledge base is tedious. This Skill automates chunked reading and structured note extraction from books and long documents. ## Core Features & Use Cases - Multi-format ingestion: Reads PDF, EPUB, MOBI, Markdown, plain text, pasted text, and public-domain URLs, converting EPUB/MOBI via pandoc or calibre. - Four extraction modes: notes (chapter-by-chapter TL;DR, concepts, quotes, action items, frameworks), summary (whole-book TL;DR plus takeaways), quotes (verbatim pull-quotes with page refs), and study (notes plus spaced-repetition Q&A cards). - Smart chunking: Splits by chapter when a TOC exists, by 50-page blocks for PDFs, or by 30,000-character blocks for text, saving a chunking plan as JSON. - Second-brain capture: Optionally writes the final notes to a second-brain vault as a highlights file with wiki cross-reference suggestions, and can render output to PDF or HTML via pandoc. - Use Case: You have a 300-page business book PDF. Run the notes mode to get per-chapter summaries, verbatim quotes with page numbers, and action items, then capture the result into your Obsidian vault for later compilation into wiki pages. ## Quick Start Ask the assistant to read the book at a given file path and extract chapter-by-chapter notes with key takeaways and quotes.