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Configure persistent memory search for Moltbot/Clawdbot.
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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Original instructions from the publisher’s SKILL.md
# 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`):
```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:
```markdown
# 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:
```markdown
# 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:
```markdown
## 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
```json
{
"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. 🐘