Audit, clean, and optimize Clawdbot's vector memory (LanceDB). Use when memory is bloated with junk, token usage is high from irrelevant auto-recalls, or setting up memory maintenance automation.
Install
Documentation
Memory Hygiene
Keep vector memory lean. Prevent token waste from junk memories.
Quick Commands
Audit: Check what's in memorymemory_recall query="*" limit=50
Wipe: Clear all vector memory
rm -rf ~/.clawdbot/memory/lancedb/
Then restart gateway: clawdbot gateway restart
memory_store text="<fact>" category="preference|fact|decision" importance=0.9
Config: Disable Auto-Capture
The main source of junk is autoCapture: true. Disable it:
{
"plugins": {
"entries": {
"memory-lancedb": {
"config": {
"autoCapture": false,
"autoRecall": true
}
}
}
}
}
Use gateway action=config.patch to apply.
What to Store (Intentionally)
✅ Store:
- -User preferences (tools, workflows, communication style)
- -Key decisions (project choices, architecture)
- -Important facts (accounts, credentials locations, contacts)
- -Lessons learned
❌ Never store:
- -Heartbeat status ("HEARTBEAT_OK", "No new messages")
- -Transient info (current time, temp states)
- -Raw message logs (already in files)
- -OAuth URLs or tokens
Monthly Maintenance Cron
Set up a monthly wipe + reseed:
cron action=add job={
"name": "memory-maintenance",
"schedule": "0 4 1 * *",
"text": "Monthly memory maintenance: 1) Wipe ~/.clawdbot/memory/lancedb/ 2) Parse MEMORY.md 3) Store key facts to fresh LanceDB 4) Report completion"
}
Storage Guidelines
When using memory_store:
- -Keep text concise (<100 words)
- -Use appropriate category
- -Set importance 0.7-1.0 for valuable info
- -One concept per memory entry
Launch an agent with Memory Hygiene on Termo.