Hybrid memory strategy combining OpenClaw's built-in vector memory with Graphiti temporal knowledge graph. Use when you need to recall past context, answer temporal questions ("when did X happen?"), or search memory files. Provides decision framework for when to use memory_search vs Graphiti.
数据来源：ClawHub。 在 ClawSkills 查看
选择你使用的 Agent
方法一：命令行安装（推荐）
推荐（无需提前安装 clawhub）
npx clawhub@latest --dir ~/.claude/skills install hybrid-memory或使用 clawhub CLI（需提前安装）
clawhub --dir ~/.claude/skills install hybrid-memory⚠️ 需要 Node.js 18+，没有 Node？请使用下方方法二直接下载 ZIP。 安装 Node.js →
方法二：手动下载安装（无需 Node）
下载 ZIP，解压后将文件夹放到以下路径，重启 Agent 即可：
安装路径
~/.claude/skills/hybrid-memory/💡解压后将文件夹放到上方路径，重启 Agent 即可生效
--- name: hybrid-memory description: Hybrid memory strategy combining OpenClaw's built-in vector memory with Graphiti temporal knowledge graph. Use when you need to recall past context, answer temporal questions ("when did X happen?"), or search memory files. Provides decision framework for when to use memory_search vs Graphiti. ---
Two memory systems, each with different strengths. Use both.
| Question Type | Tool | Example | |--------------|------|---------| | Document content | memory_search | "What's in GOALS.md?" | | Curated notes | memory_search | "What are our project guidelines?" | | Temporal facts | Graphiti | "When did we set up Slack?" | | Conversations | Graphiti | "What did the user say last Tuesday?" | | Entity tracking | Graphiti | "What projects involve Alice?" |
Semantic search over markdown files (MEMORY.md, memory/*/.md).
memory_search query="your question"Then use memory_get to read specific lines if needed.
Search for facts with time awareness:
graphiti-search.sh "your question" GROUP_ID 10Log important facts:
graphiti-log.sh GROUP_ID user "Name" "Fact to remember"Common group IDs:
main-agent — Primary agentuser-personal — User's personal contextWhen answering questions about past context:
memory_searchAdd to your AGENTS.md:
### Memory Recall (Hybrid)
**Temporal questions** ("when?", "what changed?", "last Tuesday"):graphiti-search.sh "query" main-agent 10
**Document questions** ("what's in X?", "find notes about Y"):memory_search query="your query"
When answering past context: check Graphiti for temporal, memory_search for docs.Full setup guide: https://github.com/clawdbrunner/openclaw-graphiti-memory
Part 1: OpenClaw Memory — Configure embedding provider (Gemini recommended) Part 2: Graphiti — Deploy Docker stack, install sync daemons
安装 Hybrid Memory 后，可以对 AI 说这些话来触发它
Help me get started with Hybrid Memory
Explains what Hybrid Memory does, walks through the setup, and runs a quick demo based on your current project
Use Hybrid Memory to hybrid memory strategy combining OpenClaw's built-in vector memory ...
Invokes Hybrid Memory with the right parameters and returns the result directly in the conversation
What can I do with Hybrid Memory in my documents & notes workflow?
Lists the top use cases for Hybrid Memory, with example commands for each scenario
将技能文件夹放到 ~/.claude/skills/hybrid-memory/ 目录（个人级，所有项目可用），或 .claude/skills/hybrid-memory/（项目级）。重启 AI 客户端后，用 /hybrid-memory 主动调用，或让 AI 根据上下文自动发现并使用。
Hybrid Memory 支持 Claude、Cursor、OpenClaw，可与这些 AI 平台无缝集成，扩展其能力。
Hybrid Memory 可免费安装使用。请查阅仓库了解许可证信息。
Hybrid memory strategy combining OpenClaw's built-in vector memory with Graphiti temporal knowledge graph. Use when you need to recall past context, answer temporal questions ("when did X happen?"), or search memory files. Provides decision framework for when to use memory_search vs Graphiti.
Hybrid Memory 属于「Documents & Notes」分类，该分类的技能帮助 AI 智能体在此领域执行专业任务。
Automate my documents & notes tasks using Hybrid Memory
Identifies repetitive steps in your workflow and sets up Hybrid Memory to handle them automatically