---

name: memory-setup description: 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.

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

| Setting | Purpose | Recommended | |---------|---------|-------------| | enabled | Turn on memory search | true | | provider | Embedding provider | "voyage" | | sources | What to index | ["memory", "sessions"] | | indexMode | When to index | "hot" (real-time) | | minScore | Relevance threshold | 0.3 (lower = more results) | | maxResults | Max snippets returned | 20 |

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. 🐘