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agent-memory-systems

Design memory for AI agents — short-term context, long-term stores, retrieval strategies, and memory-augmented reasoning. Use when an agent must remember facts, learn preferences, or stay coherent across sessions.

skills/agent-memory-systems/SKILL.md

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# Agent Memory Systems

Memory is what turns a stateless chatbot into an agent that learns. A memory system has three 
parts: what gets stored, how it's retrieved, and how it's forgotten or updated. Design all three 
deliberately.

## Overview

Short-term memory is the working context: the conversation, recent tool outputs, the current plan. 
It's fast, exact, and bounded by the context window. Long-term memory persists across sessions: 
facts about the user, project state, learned preferences, past decisions. The bridge between them 
is retrieval — deciding what to recall and when — and write policies — deciding what deserves 
to be remembered. The best systems treat memory as a living document with explicit update and 
expiry rules, not an append-only log.