clawdbrunner/hybrid-memory
skill/SKILL.md
Recalls past conversations, retrieves stored facts, and searches documents using OpenClaw QMD vector memory and Graphiti temporal knowledge graph. Use when the user asks to remember something, recall a previous discussion, look up what was said before, find prior context, check conversation history, or retrieve a stored fact or document.
$ install --global
skillsauthnpx skillsauth add clawdbrunner/openclaw-graphiti-memory hybrid-memoryInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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TrivyContainer and dependency vulnerability scanner
95%
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SemgrepStatic code analysis for vulnerabilities
95%
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mcp-scan (Snyk)Model Context Protocol security validation
95%
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Snyk (dep)Open source security scanning
50%
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Socket.devSupply chain security analysis
50%
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VirusTotalMulti-engine malware detection
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CrowdStrikeAdvanced threat intelligence
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OSV-ScannerOpen Source Vulnerability database check
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OWASP Dep-Check
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Last scanned: Jun 4, 2026, 3:40 AM126.2s1 file scanned
SKILL.md
- name:
- hybrid-memory
- description:
- Recalls past conversations, retrieves stored facts, and searches documents using OpenClaw QMD vector memory and Graphiti temporal knowledge graph. Use when the user asks to remember something, recall a previous discussion, look up what was said before, find prior context, check conversation history, or retrieve a stored fact or document.
Hybrid Memory System
Combines two memory backends into a single recall layer:
- QMD (Vector Store): Retrieves documents, specs, and full-text content by semantic similarity.
- Graphiti (Knowledge Graph): Retrieves temporal facts, entity relationships, and cross-agent knowledge.
Primary Tool
For most memory queries, use the hybrid search script. It queries both systems in parallel and merges results.
~/.openclaw/scripts/memory-hybrid-search.sh "your query"
Optional flags:
[group_id]— Specify agent group (default:openclaw-main)--json— Output JSON for programmatic use
Specific Tools (Advanced)
Use these when the hybrid script returns no results, or when you need granular control over a single backend.
Graphiti Only (Temporal/Facts)
Search for specific temporal facts:
~/.openclaw/scripts/graphiti-search.sh "your question" openclaw-main 10
Log new facts (IMPORTANT — do this after key conversations or decisions):
~/.openclaw/scripts/graphiti-log.sh openclaw-main user "Name" "Fact to remember"
QMD Only (Deep Document Search)
If you need more results or specific file filtering:
qmd search "query" -n 10
Recall Pattern
- User asks question ("What was the plan for the project?")
- Run Hybrid Search (
~/.openclaw/scripts/memory-hybrid-search.sh "plan for the project") - Synthesize Answer from both the temporal facts and document snippets found.
- If needed: Use
readto get the full content of a file found in the QMD results. - If no results: Retry with broader terms, try Graphiti direct (
graphiti-search.sh), or widen QMD search (qmd search "query" -n 20).
Proactive Logging
Keep the knowledge graph current by logging important facts after they occur:
- After the user shares a preference, decision, or key fact
- After completing a task with outcomes worth remembering
- After learning new entity relationships (people, projects, systems)
~/clawd/scripts/graphiti-log.sh clawdbot-main user "UserName" "User decided to use PostgreSQL for the new service"
When to Use Which
| Question Type | Use |
|---------------|-----|
| "What's in GOALS.md?" | Hybrid search → read file |
| "When did we discuss X?" | Hybrid search (Graphiti results) |
| "What did I say last Tuesday?" | Graphiti direct |
| "Find notes about architecture" | Hybrid search (QMD results) |
| "Remember that I prefer dark mode" | graphiti-log.sh to store the fact |
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