Compiles large documents into structured agent skills with on-demand chapter loading to reduce token usage compared to raw context dumping. Supports text extraction from multiple formats and is designed for integration with coding agent CLIs.
Project overview
Documented to reduce token usage 24x-51x by compiling documents into structured skills, paying extraction costs only once while preventing hallucinations.
Project type
AI Coding
Deployment
Refer to project documentation
License
MIT
Best for
Developers who need to query specific topics within large technical books or documents and want to reduce token usage during AI-assisted coding or research.
Key capabilities
Extracts text and structure from PDF, EPUB, DOCX, TXT, Markdown, HTML, RTF, and MOBI files.
Folds new documents into an existing generated skill folder to merge knowledge incrementally.
Provides a standalone command-line interface for the text extraction engine without registering the agent skill.
Limitations and risks
Publishing or sharing a generated skill of a copyrighted work can infringe the rights holder.
Getting started
Install via pip or git clone. Run the command-line tool against a document, such as 'book-to-skill ~/path/to/book.pdf --mode text', to test extraction without registering the skill. The installation difficulty is documented as easy.
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