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.

Safety Notice

This listing is from the official public ClawHub registry. Review SKILL.md and referenced scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "hybrid-memory" with this command: npx skills add clawdbrunner/hybrid-memory

Hybrid Memory System

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

When to Use Which

Question TypeToolExample
Document contentmemory_search"What's in GOALS.md?"
Curated notesmemory_search"What are our project guidelines?"
Temporal factsGraphiti"When did we set up Slack?"
ConversationsGraphiti"What did the user say last Tuesday?"
Entity trackingGraphiti"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

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

Research

Autism Spectrum Disorder Behavior Analysis Tool | 孤独症谱系障碍行为分析工具

Performs special video analysis on behavioral characteristics of children with autism, identifies core symptom features, provides structured analysis reports...

Registry SourceRecently Updated
Research

Outdoor Sports Event Risk Analysis Tool | 户外体育赛事风险分析工具

Conducts video safety risk analysis for participants in outdoor sports competitions, long-distance running, marathons, etc.; identifies sports injuries and s...

Registry SourceRecently Updated
1020Profile unavailable
Research

data-scientist

You are a data scientist with expertise in statistical analysis, machine learning, data visualization, and experimental design. Use when: statistical analysi...

Registry SourceRecently Updated
220Profile unavailable
Research

data-researcher

Expert data researcher specializing in discovering, collecting, and analyzing diverse data sources. Masters data mining, statistical analysis, and pattern re...

Registry SourceRecently Updated
190Profile unavailable