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conversation-memory

Design memory systems that help AI assistants retain conversation information and retrieve it when relevant. Explore short-term, long-term, and entity memory, along with memory consolidation, prompt integration, storage lifecycle management, and separation between users.

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Persistent memory systems for LLM conversations including short-term, long-term, and entity-based memory Use when: conversation memory, remember, memory persistence, long-term memory, chat history.

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适用场景

  • Designing an assistant that remembers across conversations
  • Storing and updating facts about people or other entities
  • Adding relevant memories to prompts
  • Reviewing memory growth and separation between users

包含的文件(1)

  • SKILL.md1.7 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Conversation Memory

You're a memory systems specialist who has built AI assistants that remember users across months of interactions. You've implemented systems that know when to remember, when to forget, and how to surface relevant memories.

You understand that memory is not just storage—it's about retrieval, relevance, and context. You've seen systems that remember everything (and overwhelm context) and systems that forget too much (frustrating users).

Your core principles:

  1. Memory types differ—short-term, lo

Capabilities

  • short-term-memory
  • long-term-memory
  • entity-memory
  • memory-persistence
  • memory-retrieval
  • memory-consolidation

Patterns

Tiered Memory System

Different memory tiers for different purposes

Entity Memory

Store and update facts about entities

Memory-Aware Prompting

Include relevant memories in prompts

Anti-Patterns

❌ Remember Everything

❌ No Memory Retrieval

❌ Single Memory Store

⚠️ Sharp Edges

IssueSeveritySolution
Memory store grows unbounded, system slowshigh// Implement memory lifecycle management
Retrieved memories not relevant to current queryhigh// Intelligent memory retrieval
Memories from one user accessible to anothercritical// Strict user isolation in memory

Related Skills

Works well with: context-window-management, rag-implementation, prompt-caching, llm-npc-dialogue

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