What problem does it solve? Finding information across large collections of local markdown notes and documentation is slow and unreliable with basic file search, especially when you need semantic similarity or ranked relevance. ## Core Features & Use Cases - Fast Keyword Search: Run BM25-ranked searches across indexed markdown collections with score thresholds, result limits, and JSON output. - Semantic and Hybrid Search: Use vector search for conceptual similarity or hybrid mode with LLM reranking for the highest-quality results. - Document Retrieval: Fetch full documents by path, ID, or glob pattern, and maintain index health with status, update, and embed commands. - Use Case: You have a knowledge base of 2,000 markdown notes and need to find every note mentioning a specific project deadline — run a scoped BM25 search against your notes collection and retrieve the matching documents instantly. ## Quick Start Search my indexed markdown notes for "quarterly review deadlines" and show me the top five matching documents.