conversation-memory
について
このスキルは、LLM会話のための永続的メモリシステムを提供し、短期記憶、長期記憶、エンティティベースの記憶を実現します。メモリの永続化、検索、統合を処理し、インタラクションを超えてコンテキストを維持します。アプリケーションがユーザーの詳細、チャット履歴、または特定のエンティティを長期間にわたって記憶する必要がある場合にご利用ください。
クイックインストール
Claude Code
推奨/plugin add https://github.com/majiayu000/claude-skill-registrygit clone https://github.com/majiayu000/claude-skill-registry.git ~/.claude/skills/conversation-memoryこのコマンドをClaude Codeにコピー&ペーストしてスキルをインストールします
ドキュメント
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:
- 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
| Issue | Severity | Solution |
|---|---|---|
| Memory store grows unbounded, system slows | high | // Implement memory lifecycle management |
| Retrieved memories not relevant to current query | high | // Intelligent memory retrieval |
| Memories from one user accessible to another | critical | // Strict user isolation in memory |
Related Skills
Works well with: context-window-management, rag-implementation, prompt-caching, llm-npc-dialogue
GitHub リポジトリ
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