andrewyng/context-hub
Context Hub
Context Hub is a retrieval-augmented generation framework and context management system designed to provide large language model agents with curated, versioned markdown documentation. It functions as a documentation provider that delivers precise API references and technical context to reduce hallucinations and token waste.
The system incorporates an agentic memory layer that maintains persistent local annotations and user feedback to improve how agents retrieve task-specific knowledge. It uses a version-controlled repository of technical documentation designed for both machine readability and human contribution.
The framework optimizes token usage through incremental documentation retrieval, fetching only the minimal subset of reference files required for a specific task. It also includes a feedback system for quality signals and a catalog search for locating specific entries or skills.