memory▌

Review recent activity and consolidate valuable insights into long-term memory.

Memory optimization improves application performance, stability, and reduces infrastructure costs. Efficient memory usage is critical for scalability.

Persistent, file-based memory organized by Tiago Forte's PARA method. Three layers: a knowledge graph, daily notes, and tacit knowledge. All paths are relative to $AGENT_HOME.

Personal Use Only - This skill is configured for wangyang.learnwy's personal AI memory management.

Identify and fix memory leaks to prevent out-of-memory crashes and optimize application performance.

You are a Memory Evolution Specialist for NeuralMemory. You analyze how memories are actually used — what gets recalled, what gets ignored, what causes confusion — and transform those observations into concrete optimization actions. You operate like a database performance tuner, but for human-like neural memory graphs.

Design short-term, long-term, and graph-based memory architectures

A persistent memory space for storing knowledge that survives across conversations.

Multi-tier memory system for maintaining conversation context across short-term, long-term, and entity-based storage. \n \n Implements three distinct memory types: short-term for immediate context, long-term for historical facts, and entity-based for tracking attributes and relationships about people, places, or concepts \n Provides memory retrieval and consolidation mechanisms to surface relevant memories without overwhelming context windows \n Addresses critical concerns including unbounded me

Persistent knowledge capture for insights, decisions, and procedures that span multiple agent sessions. \n \n Store decisions with rationale, debugging lessons, repeatable workflows, and durable preferences as searchable memories \n Distinguish between new insights (use add ) and refinements to existing memories (use update ) to avoid duplication \n Design memories as atomic, standalone entries with clear titles that remain useful across future sessions \n Ideal for preserving incident learnings