Set up durable memory for OpenClaw so the agent can recall prior decisions, preferences, and todos.

1) Prepare workspace files

In workspace root, keep:

• MEMORY.md (curated long-term memory)
• memory/YYYY-MM-DD.md (daily notes)

Optional structure:

• memory/projects/
• memory/system/
• memory/groups/

2) Enable memory search in OpenClaw config

Configure under agents.defaults.memorySearch (not top-level memorySearch).

Example:

{
  "agents": {
    "defaults": {
      "memorySearch": {
        "enabled": true,
        "provider": "local",
        "includeDefaultMemory": true,
        "maxResults": 20,
        "minScore": 0.3
      }
    }
  }
}

Notes:

• includeDefaultMemory: true indexes MEMORY.md + memory/*/.md.
• Providers: local, openai, gemini, voyage, mistral.
• If using remote provider, set corresponding API key (env var or memorySearch.remote.apiKey).

3) Restart and verify

• Restart gateway after config changes.
• Verify with:

4) Test recall behavior

Ask a question about past context, then verify the agent:

• Runs memory_search
• Uses memory_get for precise lines when needed
• Cites source path/lines when useful

5) Troubleshooting

memory_search unavailable

• Ensure agents.defaults.memorySearch.enabled = true.
• Ensure policy allows memory tools.
• Restart gateway.

low-quality matches

• Lower minScore (e.g. 0.2) to broaden hits.
• Raise maxResults (e.g. 30).
• Write more specific notes in MEMORY.md and daily logs.

local provider issues

• Confirm local model path/settings if configured.
• If needed, switch provider to remote and set API key.

6) Recommended operating rule

Before answering questions about prior work, decisions, dates, people, preferences, or todos:

• memory_search first
• memory_get second (only needed lines)
• Say you checked memory if confidence is still low

This keeps responses grounded and auditable.