V3 Memory Unification

Unifying memory consolidates disparate memory systems into a single AgentDB backend powered by HNSW vector search, enabling semantic querying and cross-agent memory sharing. This Skill implements UnifiedMemoryService to migrate SQLiteBackend and MarkdownBackend data into one indexed system supporting real-time synchronization.

Yes. This Skill includes a DataMigrator component that handles cross-backend migration from SQLiteBackend and MarkdownBackend into AgentDB with embedding generation for semantic search, while maintaining backward compatibility with existing memory managers in multi-agent systems.

HNSW indexing provides ultra-fast semantic search by storing embeddings in an optimized vector structure. This Skill configures HNSW indexing within AgentDB to enable low-latency queries across unified memory, supporting both real-time agent access and SONA learning pattern retrieval.

No. This Skill unifies memory without requiring architecture rewrites—it migrates data from existing SQLiteBackend and MarkdownBackend systems into AgentDB while preserving backward compatibility, so heterogeneous memory managers continue working during and after transition.

Embedding generation converts memory entries from disparate formats into semantic vectors indexed by HNSW. This unified representation enables consistent querying regardless of original storage format—SQL, Markdown, or custom—while enabling cross-agent memory sharing and learning pattern storage.