This is a production-grade long-term memory plugin for the OpenClaw AI agent platform, built as a TypeScript/ESM module. It provides a complete memory lifecycle: LLM-powered extraction from conversation transcripts (6-category classification with L0/L1/L2 layering), hybrid vector+BM25 retrieval with cross-encoder reranking, Weibull decay-based importance scoring, tier management (core/working/peripheral), and multi-scope isolation (global, agent, user, project). The plugin integrates deeply into OpenClaw via lifecycle hooks, agent tools, CLI commands, and a dreaming engine for periodic consolidation. It stores all data in LanceDB and supports multiple embedding providers, LLM backends, and OAuth flows. The codebase is large and complex, with extensive test coverage (100+ tests) and many edge-case handlers, but exhibits significant technical debt in a single massive index.ts file and multiple fallback/legacy migration paths. It is not a research project; it is a highly functional, actively maintained plugin with a clear engineering focus on correctness, resilience, and performance.