Obsidian + OpenClaw AI Memory System

VerifiedSafe

Set up Obsidian and OpenClaw as a persistent AI memory system. Includes file structure, vault setup, semantic search, and heartbeat-based memory maintenance.

Sby Skills Guide Bot
ProductivityIntermediate
007/23/2026
Claude Code
#obsidian#openclaw#memory-system#knowledge-graph#semantic-search

Recommended for

Our review

Set up Obsidian and OpenClaw as a persistent AI memory system, with QMD semantic search and heartbeat-based proactive maintenance.

Strengths

  • Provides persistent context across sessions by reading workspace files into the system prompt
  • Obsidian visualizes the knowledge graph for intuitive navigation
  • QMD enables on-device semantic search without loading all files into context
  • HEARTBEAT automates long-term memory distillation and maintenance

Limitations

  • Requires initial setup of multiple components (Obsidian, OpenClaw, QMD)
  • Depends on OpenClaw, which may not be available in all AI environments
  • Memory quality relies on consistent manual logging and curation
When to use it

Use this skill when the user wants their AI assistant to remember decisions and context across sessions using a file-based memory system.

When not to use it

Avoid if the user lacks access to OpenClaw or prefers a built-in memory solution.

Security analysis

Safe
Quality score95/100

The skill provides setup instructions for Obsidian, OpenClaw, and QMD. It suggests shell commands (e.g., qmd collection add, qmd embed) that are legitimate and used for indexing/search, with no destructive or exfiltrating behavior. No code is obfuscated or dangerous.

No concerns found

Examples

Initialize memory workspace
Set up an Obsidian vault pointed at my ~/clawd workspace and configure OpenClaw to inject MEMORY.md and daily logs into the system prompt.
Configure HEARTBEAT for memory maintenance
Create a HEARTBEAT.md file that reminds me every three days to review recent daily logs and distill key insights into MEMORY.md.
Add QMD semantic search
Install and configure QMD for semantic search over my memory files, then show me how to query it from within OpenClaw using mcporter.

name: obsidian-openclaw-memory description: Set up Obsidian + OpenClaw as a living AI memory system. Use when helping users configure their workspace so their AI assistant remembers context across sessions, builds a knowledge graph, and proactively maintains memory. Covers file structure, Obsidian vault setup, QMD semantic search, and heartbeat-based memory maintenance.

Obsidian + OpenClaw Memory System

Overview

The AI doesn't have memory — it reads memory. OpenClaw injects workspace files into the system prompt at session start, giving the AI persistent context across sessions. Obsidian visualizes the knowledge graph. QMD provides semantic search so the AI finds relevant context without loading everything.

Three components:

  • OpenClaw — reads workspace files at session start (injected into system prompt)
  • Obsidian — vault pointed at the workspace; Graph View shows connections between files
  • QMD — on-device semantic search; find relevant files without loading them all

File Structure

See references/file-structure.md for the full annotated file tree.

Core files:

| File/Folder | Purpose | |---|---| | MEMORY.md | Curated long-term memory (distilled from daily logs) | | memory/YYYY-MM-DD.md | Raw daily session logs | | second-brain/ | Structured knowledge base (concepts, journal, documents) | | directives/ | SOPs and workflows | | HEARTBEAT.md | Drives proactive AI behavior between sessions | | AGENTS.md | How the AI should operate in this workspace | | USER.md | Context about the human | | SOUL.md | AI persona and tone |

How OpenClaw Reads Files

OpenClaw's workspace injection reads files listed in its config and prepends them to the system prompt. This means:

  • Files in the workspace root are always available
  • The AI "wakes up" each session already knowing what's in those files
  • Updating a file = updating what the AI knows next session

Key principle: write important things to files, not just say them in chat.

Obsidian Setup

  1. Create vault pointing to your ~/clawd workspace folder (File → Open Vault → Open Folder as Vault)
  2. Enable Graph View (Ctrl/Cmd+G) — see how memory files link to each other
  3. Install plugins:
    • Dataview — query memory files like a database (TABLE, LIST, TASK queries)
    • Templater — daily note templates for memory/YYYY-MM-DD.md
  4. Daily note template (via Templater):
    # <% tp.date.now("YYYY-MM-DD") %>
    
    ## Session Log
    
    ## Decisions Made
    
    ## Things to Remember
    
  5. Dataview query to surface recent memories:
    LIST FROM "memory" SORT file.name DESC LIMIT 7
    

QMD Semantic Search Setup

# Add workspace to QMD index
qmd collection add ~/clawd --name clawd

# Generate embeddings (run after adding new files)
qmd embed

# Search from within OpenClaw
mcporter call qmd.vsearch query="what did we decide about X"
mcporter call qmd.query query="project status"

This lets the AI find relevant context without loading every file into the context window.

Heartbeat-Based Memory Maintenance

HEARTBEAT.md drives proactive AI behavior. OpenClaw polls it on a schedule and acts on what it finds.

Example HEARTBEAT.md:

## Memory Maintenance
- [ ] Review memory/ files from last 3 days
- [ ] Distill key insights into MEMORY.md
- [ ] Remove outdated entries from MEMORY.md

The AI will pick this up, review recent logs, and update long-term memory — like a human reviewing their journal and updating their mental model.

Schedule: Add a heartbeat cron or configure OpenClaw's heartbeat interval. Every few days is sufficient for memory distillation.

Best Practices

  1. Write it down — if you want the AI to remember something next session, say "write this to memory" or update memory/YYYY-MM-DD.md directly
  2. Keep MEMORY.md curated — it's the distilled essence, not a dump. Short, high-signal entries.
  3. Daily logs are rawmemory/YYYY-MM-DD.md is for raw session notes; don't worry about formatting
  4. Use directives/ for SOPs — repeatable workflows go here so the AI can follow them consistently
  5. Link files in Obsidian — use [[MEMORY]] wiki-links to build the graph view
  6. Re-embed after adding files — run qmd embed after adding significant new content

Architecture Diagram

See assets/architecture.png for a visual overview of how the three components interact.

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