Vector Memory Overview High-performance vector search using HNSW (Hierarchical Navigable Small World) graphs for pattern storage and retrieval, combined with a knowledge graph for relational reasoning. When to Use - Retrieving similar patterns from execution history - Building and querying knowledge graphs for project context - Managing cross-session memory across project/local/user scopes - Fast similarity search for routing decisions HNSW Performance - Search latency: 61 microseconds - Query throughput: 16,400 QPS - Configurable embedding dimensions (default: 128) Knowledge Graph - PageRank…