Conversation Memory

by davila78da17d671b6fNo license32K starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated today

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.

Instructions onlyAI & Agents
AI-generated overview

Guides design of persistent memory systems for LLM conversations, covering short-term, long-term and entity memory.

What it does
This skill provides guidance on building persistent memory for LLM conversations, covering short-term, long-term and entity-based memory. It describes tiered memory designs, entity fact storage, memory-aware prompting, and retrieval and consolidation patterns. It also lists anti-patterns and sharp edges such as unbounded memory growth, irrelevant retrieval and cross-user memory leakage. It is instructions only and produces no files or scripts.
When to use it
Use it when designing or reviewing how an AI assistant should remember users and prior interactions across sessions. It fits work on memory persistence, chat history handling, and surfacing relevant memories in prompts.
Requirements
No tools, packages or credentials are required; it is instructions only and ships no scripts.

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

Source and attribution

Source:davila7/claude-code-templatesincli-tool/components/skills/ai-research/conversation-memoryat commit8da17d6

License: No license

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Conversation Memory Agent Skill | SourceWeft