Provides a 'library keeper' sub-agent that ingests PDF/EPUB books and answers questions grounded in them via local embedding search, with deterministic classification and knowledge gap logging.
Enables AI agents to browse, search, and retrieve papers from a local research library with read-only access, supporting multiple formats and automatic indexing.
Provides AI agents with research capabilities for local Calibre e-book libraries, including fulltext search across titles, ISBNs, and comments, plus structured excerpt retrieval from books.
Enables AI assistants to search and query PDF documents through a local RAG system with vector embeddings. Provides semantic document search capabilities while keeping all data stored locally without external dependencies.
Enables coding agents to verify verbatim quotes against a local corpus of scientific PDFs, returning exact matches with page locators or typed refusals without using an LLM.