Large Document Reader

Split long documents (books, reports, theses, legal filings, technical manuals) into structured chapters or sections for systematic, chapter-by-chapter reading and analysis within LLM context windows.

Overview

Large Language Models have finite context windows, and even models with 100K+ token limits can lose accuracy on information buried in the middle of very long inputs. Academic researchers frequently work with documents that exceed practical context limits: doctoral theses (200+ pages), government reports, book-length monographs, legal case compilations, and multi-volume technical standards.

This skill provides a systematic approach to splitting large documents into semantically meaningful chapters or sections, maintaining cross-references between parts, and reading each section with full comprehension. Rather than naive fixed-size chunking that breaks mid-sentence or mid-argument, this approach respects document structure -- headings, chapter breaks, section markers, and logical boundaries.

The result is a structured reading experience where each chapter is analyzed in full context, summaries are maintained across sessions, and the reader can navigate directly to any section of interest. This is especially valuable for literature reviews, systematic reviews, and comprehensive document analysis tasks.

Document Splitting Strategy

Hierarchy of Split Points

Documents should be split at the highest-level structural boundary that keeps each chunk within the target size:

| Priority | Boundary Type | Markers |