Hippocampus Memory Core
Use this skill when you need long-term memory that survives the current turn.
Use It For
- - storing key decisions and facts that should outlive the current session
- searching past architecture, deployment, or debugging context
- creating snapshots before risky changes
- restoring memory after migration or environment reset
Preferred Flow
- 1. Check that Hippocampus configuration is present.
- Store only high-signal facts, not raw transcript spam.
- Search memory before repeating costly investigation.
- Snapshot before major refactors or rollout changes.
- Restore only into the correct agent or workspace scope.
Guidance
- - Prefer deterministic retrieval over ad hoc summaries.
- Keep memory namespaced by workspace and agent.
- Use metadata to mark project, topic, and task boundaries.
- Treat memory as durable infrastructure, not scratchpad overflow.
- If configuration is missing, send the user to INLINECODE0
instead of asking for a raw API key first.
Related
- -
hippocampus-openclaw-onboarding for first-time setup - INLINECODE2 for isolated child-agent memory
- INLINECODE3 for native OpenClaw lifecycle integration
海马体记忆核心
当您需要能够在当前对话轮次结束后依然存留的长期记忆时，请使用此技能。
适用场景
- - 存储应超越当前会话周期的关键决策和事实
- 检索过去的架构、部署或调试上下文
- 在有风险变更前创建快照
- 在迁移或环境重置后恢复记忆
推荐流程
- 1. 确认海马体配置已就绪。
- 仅存储高价值事实，而非原始对话记录垃圾信息。
- 在重复进行代价高昂的调查前先搜索记忆。
- 在重大重构或版本发布变更前创建快照。
- 仅恢复到正确的智能体或工作空间范围内。
使用指南
- - 优先采用确定性检索，而非临时性摘要。
- 按工作空间和智能体对记忆进行命名空间隔离。
- 使用元数据标记项目、主题和任务边界。
- 将记忆视为持久化基础设施，而非草稿本溢出区。
- 如果配置缺失，请引导用户前往 hippocampus-openclaw-onboarding，而非直接索要原始 API 密钥。
相关技能
- - hippocampus-openclaw-onboarding 用于首次设置
- hippocampus-subagent-memory 用于隔离的子智能体记忆
- @hippocampus/openclaw-context-engine 用于原生 OpenClaw 生命周期集成
