How does OpenClaw memory work?
決定的な回答
OpenClaw memory stores conversations, preferences, and extracted facts as vector embeddings in a dedicated memory store. When a new conversation starts, the agent performs semantic search to retrieve the most relevant memories — not keyword matching. This means OpenClaw can recall a preference from months ago based on meaning, not exact words. Memories are scoped per user, per channel, or globally depending on your configuration.
ステップバイステップガイド
- 1Enable the memory system on your deployed OpenClaw agent via the FetchOpenClaws dashboard.
- 2Configure memory scope: per-user (each person has their own memory), per-channel, per-team, or global.
- 3Set retention policies: how long memories are kept and which types of information to store.
- 4The agent automatically extracts facts, preferences, and key context from every conversation.
- 5On new conversations, the agent runs semantic search against stored memories to inject relevant context.
- 6Review and manage memories through the memory dashboard — edit, delete, or export as needed.
プロンプト例
Enable persistent memory for my customer support agent. Remember each customer's purchase history, support ticket history, and stated preferences. Scope memory per user and retain for 12 months.
よくある落とし穴
- Not configuring memory scope — global memory can mix contexts between different users
- Storing too much — configure filters to save meaningful context, not every message
- Forgetting GDPR obligations — configure retention limits and enable user deletion requests
- Not testing memory recall before production — verify relevant memories surface correctly
よくある質問
ユーザーフィードバック
スタートアップ CTO
“回答ガイドが正しいデプロイ戦略の選択を助け、1時間以内にエージェントを稼働させました。”
DevOps エンジニア
“注意事項リストが本番障害を引き起こす設定ミスから救ってくれました。”
エージェンシーディレクター
“関連ツールリンクでこれらのページが実用的に — 一回のセッションで質問からデプロイまで。”