Provides LLM agents with a toolset for reviewing S1000D technical publications, including XML schema validation, cross-reference and applicability checks, skeleton generation, and AI-suggested fixes.
Provides AI agents with local file-processing capabilities for token counting, RAG chunking, CSV/JSON conversion, QR generation, and more, while keeping documents private on the user's machine.
Enables Large Language Models to safely browse and interact with local file systems through secure directory listing, file reading, and content search capabilities. Built with comprehensive security controls and high-performance handling of large directories and files.
Lets AI agents know things about files without reading them, supporting outline, search, slicing, SQL, log clustering, diffs, validation, and extraction for formats like PDF, DOCX, PPTX, XLSX, CSV, logs, and code.
Enables agents to inspect PDF, Microsoft Office, and Apple iWork documents without rendering them, providing page/slide counts, metadata, security signals, structure, and integrity as deterministic JSON via typed tools and batch operations.