memory-setup
Installation
Summary
Configure persistent memory search for Moltbot/Clawdbot agents to retain context across sessions.
- Add
memorySearchconfig block with provider (Voyage, OpenAI, or local), sources (memory files and/or sessions), and relevance thresholds - Create a workspace structure with
MEMORY.mdfor curated long-term facts andmemory/logs/for daily timestamped logs - Supports three embedding providers; Voyage recommended but local option available without API keys
- Includes troubleshooting for common issues: verify config is enabled, restart gateway, and adjust
minScoreandmaxResultsif results lack relevance
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):
{
"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 embeddingslocal— Local embeddings (no API needed)
Source Options
memory— MEMORY.md + memory/*.md filessessions— Past conversation transcriptsboth— 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?
- 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:
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. 🐘