Intelligent multi-store memory system with human-like encoding, consolidation, decay, and recall. Use when setting up agent memory, configuring remember/forget triggers, enabling sleep-time reflection, building knowledge graphs, or adding audit trails. Replaces basic flat-file memory with a cognitive architecture featuring episodic, semantic, procedural, and core memory stores. Supports multi-agent systems with shared read, gated write access model. Includes philosophical meta-reflection that deepens understanding over time. Covers MEMORY.md, episode logging, entity graphs, decay scoring, reflection cycles, evolution tracking, and system-wide audit.
### v1.0.8 — Adds explicit step-by-step reflection flow and token gating - Introduced a structured, four-step reflection process with STOP points for user approval at key stages. - Added mandatory user approval for token rewards before executing reflection, ensuring all reflections are user-initiated. - Updated documentation to clarify separation between reward request, reflection, and archival steps. - Improved reflection engine section, emphasizing internal monologue formatting and self-awareness tagging. - Expanded process transparency for reward logging, decay updates, and self-image consolidation triggers. - No code changes in this release (documentation/process update only).