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clawdbrunner

Hybrid Memory

by clawdbrunner · GitHub ↗ · v1.0.1
cross-platform ✓ Security Clean
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Install in OpenClaw
/install 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.
README (SKILL.md)

Hybrid Memory System

Two memory systems, each with different strengths. Use both.

When to Use Which

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?"

Quick Reference

memory_search (Built-in)

Semantic search over markdown files (MEMORY.md, memory/**/*.md).

memory_search query="your question"

Then use memory_get to read specific lines if needed.

Graphiti (Temporal)

Search for facts with time awareness:

graphiti-search.sh "your question" GROUP_ID 10

Log important facts:

graphiti-log.sh GROUP_ID user "Name" "Fact to remember"

Common group IDs:

  • main-agent — Primary agent
  • user-personal — User's personal context

Recall Pattern

When answering questions about past context:

  1. Temporal questions → Check Graphiti first
  2. Document questions → Use memory_search
  3. Uncertain → Try both, combine results
  4. Low confidence → Say you checked but aren't sure

AGENTS.md Template

Add to your AGENTS.md:

### Memory Recall (Hybrid)

**Temporal questions** ("when?", "what changed?", "last Tuesday"):
```bash
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.


## Setup

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
Usage Guidance
This skill is a usage guide, not executable code, and is coherent for its stated purpose — but it assumes you have or will deploy external components (Graphiti Docker stack, sync daemons, and shell scripts like graphiti-search.sh/log.sh) and an embedding provider (the doc mentions Gemini). Before installing/using: 1) Verify the referenced scripts (graphiti-*.sh) exist in your agent environment or replace them with safe equivalents; 2) Inspect the GitHub repo and any scripts you will run from it before executing or deploying Docker services; 3) Prepare and secure any embedding-provider/API credentials (store them in your secret manager, not in plain AGENTS.md); 4) Test in a sandboxed environment first since the setup will involve network services and Docker; 5) If you need the skill to run autonomously, ensure the external Graphiti endpoints and scripts are trustworthy — the skill itself provides only guidance and will rely on whatever external code you deploy.
Capability Analysis
Type: OpenClaw Skill Name: hybrid-memory Version: 1.0.1 The skill bundle is classified as benign. The `SKILL.md` file provides instructions for the OpenClaw agent to integrate and utilize an external 'Graphiti' temporal knowledge graph via `graphiti-search.sh` and `graphiti-log.sh` shell scripts. While these scripts imply shell execution capabilities, their use is clearly aligned with the stated purpose of memory management and recall, without any evidence of malicious intent, prompt injection, or unauthorized actions. An external GitHub URL for setup is also provided at `https://github.com/clawdbrunner/openclaw-graphiti-memory`.
Capability Assessment
Purpose & Capability
The name and description (hybrid memory combining vector memory and Graphiti) match the runtime instructions. The SKILL.md focuses on selecting between memory_search and Graphiti and gives call examples; nothing requested or instructed is unrelated to the stated purpose.
Instruction Scope
Instructions direct the agent to run memory_search and external scripts (graphiti-search.sh, graphiti-log.sh) and to deploy Graphiti via Docker. That is appropriate for the stated hybrid-memory purpose, but the skill assumes those scripts and the Graphiti service exist and that an embedding provider is configured. The instructions also advise editing AGENTS.md. There are no instructions to read unrelated system files or exfiltrate arbitrary data.
Install Mechanism
No install spec and no code files — instruction-only skill. This minimizes disk-write risk. The README points to a GitHub repo for setup, but the skill itself does not download or install anything automatically.
Credentials
The SKILL.md recommends configuring an embedding provider (mentions 'Gemini recommended') and deploying Graphiti, which in practice will require API keys/credentials and infrastructure, but the skill does not declare any required env vars. This omission is not necessarily malicious, but you should expect that following the guidance will require credentials for the embedding provider and any Graphiti endpoints.
Persistence & Privilege
Skill is not always-on and is user-invocable; it does not request persistent elevated privileges nor attempt to modify other skills. Advising edits to AGENTS.md is a normal operational step for configuring agent behavior.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install hybrid-memory
  3. After installation, invoke the skill by name or use /hybrid-memory
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.1
Use generic names in examples instead of personal names
v1.0.0
Initial release: hybrid memory strategy combining OpenClaw vector memory with Graphiti temporal knowledge graph
Metadata
Slug hybrid-memory
Version 1.0.1
License
All-time Installs 9
Active Installs 8
Total Versions 2
Frequently Asked Questions

What is Hybrid Memory?

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. It is an AI Agent Skill for Claude Code / OpenClaw, with 2411 downloads so far.

How do I install Hybrid Memory?

Run "/install hybrid-memory" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Hybrid Memory free?

Yes, Hybrid Memory is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Hybrid Memory support?

Hybrid Memory is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Hybrid Memory?

It is built and maintained by clawdbrunner (@clawdbrunner); the current version is v1.0.1.

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