memory-setup

Enable and configure Moltbot/Clawdbot memory search for persistent context. Use when setting up memory, fixing "goldfish brain," or helping users configure memorySearch in their config. Covers MEMORY.md, daily logs, and vector search setup.

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Install skill "memory-setup" with this command: npx skills add sundial-org/awesome-openclaw-skills/sundial-org-awesome-openclaw-skills-memory-setup

Memory Setup Skill

Transform your agent from goldfish to elephant. This skill helps configure persistent memory for Moltbot/Clawdbot.

Quick Setup

1. Enable Memory Search in Config

Add to ~/.clawdbot/clawdbot.json (or moltbot.json):

{
  "memorySearch": {
    "enabled": true,
    "provider": "voyage",
    "sources": ["memory", "sessions"],
    "indexMode": "hot",
    "minScore": 0.3,
    "maxResults": 20
  }
}

2. Create Memory Structure

In your workspace, create:

workspace/
├── MEMORY.md              # Long-term curated memory
└── memory/
    ├── logs/              # Daily logs (YYYY-MM-DD.md)
    ├── projects/          # Project-specific context
    ├── groups/            # Group chat context
    └── system/            # Preferences, setup notes

3. Initialize MEMORY.md

Create MEMORY.md in workspace root:

# MEMORY.md — Long-Term Memory

## About [User Name]
- Key facts, preferences, context

## Active Projects
- Project summaries and status

## Decisions & Lessons
- Important choices made
- Lessons learned

## Preferences
- Communication style
- Tools and workflows

Config Options Explained

SettingPurposeRecommended
enabledTurn on memory searchtrue
providerEmbedding provider"voyage"
sourcesWhat to index["memory", "sessions"]
indexModeWhen to index"hot" (real-time)
minScoreRelevance threshold0.3 (lower = more results)
maxResultsMax snippets returned20

Provider Options

  • voyage — Voyage AI embeddings (recommended)
  • openai — OpenAI embeddings
  • local — Local embeddings (no API needed)

Source Options

  • memory — MEMORY.md + memory/*.md files
  • sessions — Past conversation transcripts
  • both — Full context (recommended)

Daily Log Format

Create memory/logs/YYYY-MM-DD.md daily:

# YYYY-MM-DD — Daily Log

## [Time] — [Event/Task]
- What happened
- Decisions made
- Follow-ups needed

## [Time] — [Another Event]
- Details

Agent Instructions (AGENTS.md)

Add to your AGENTS.md for agent behavior:

## Memory Recall
Before answering questions about prior work, decisions, dates, people, preferences, or todos:
1. Run memory_search with relevant query
2. Use memory_get to pull specific lines if needed
3. If low confidence after search, say you checked

Troubleshooting

Memory search not working?

  1. Check memorySearch.enabled: true in config
  2. Verify MEMORY.md exists in workspace root
  3. Restart gateway: clawdbot gateway restart

Results not relevant?

  • Lower minScore to 0.2 for more results
  • Increase maxResults to 30
  • Check that memory files have meaningful content

Provider errors?

  • Voyage: Set VOYAGE_API_KEY in environment
  • OpenAI: Set OPENAI_API_KEY in environment
  • Use local provider if no API keys available

Verification

Test memory is working:

User: "What do you remember about [past topic]?"
Agent: [Should search memory and return relevant context]

If agent has no memory, config isn't applied. Restart gateway.

Full Config Example

{
  "memorySearch": {
    "enabled": true,
    "provider": "voyage",
    "sources": ["memory", "sessions"],
    "indexMode": "hot",
    "minScore": 0.3,
    "maxResults": 20
  },
  "workspace": "/path/to/your/workspace"
}

Why This Matters

Without memory:

  • Agent forgets everything between sessions
  • Repeats questions, loses context
  • No continuity on projects

With memory:

  • Recalls past conversations
  • Knows your preferences
  • Tracks project history
  • Builds relationship over time

Goldfish → Elephant. 🐘

Source Transparency

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