Agent skill
memory-hygiene
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 this agent skill to your Project
npx add-skill https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/memory-hygiene
SKILL.md
Memory Hygiene
Keep vector memory lean. Prevent token waste from junk memories.
Quick Commands
Audit: Check what's in memory
memory_recall query="*" limit=50
Wipe: Clear all vector memory
rm -rf ~/.clawdbot/memory/lancedb/
Then restart gateway: clawdbot gateway restart
Reseed: After wipe, store key facts from MEMORY.md
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
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