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:
code
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?
- •Check
memorySearch.enabled: truein config - •Verify MEMORY.md exists in workspace root
- •Restart gateway:
clawdbot gateway restart
Results not relevant?
- •Lower
minScoreto0.2for more results - •Increase
maxResultsto30 - •Check that memory files have meaningful content
Provider errors?
- •Voyage: Set
VOYAGE_API_KEYin environment - •OpenAI: Set
OPENAI_API_KEYin environment - •Use
localprovider if no API keys available
Verification
Test memory is working:
code
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. 🐘