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.

Keep vector memory lean. Prevent token waste from junk memories.

Quick Commands

Audit: Check what's in memory

text

memory_recall query="*" limit=50

Wipe: Clear all vector memory

bash

rm -rf ~/.clawdbot/memory/lancedb/

Then restart gateway: clawdbot gateway restart

Reseed: After wipe, store key facts from MEMORY.md

text

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:

json

{
  "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:

text

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