| name | memory-consolidation |
| description | Periodic "sleep-like" memory optimization. Detects patterns, resolves conflicts, applies decay, and transfers knowledge across contexts. |
| metadata | {"clawdbot":{"requires":{"bins":["python3"]}}} |
| user-invocable | true |
Memory Consolidation
Cross-session learning through periodic memory optimization, inspired by how biological sleep consolidates memories.
When to Run
| Frequency | Type | Duration | Purpose |
|---|
| Daily | Light | ~2 min | Health check, quick cleanup |
| Weekly | Standard | ~10 min | Full consolidation |
| Monthly | Deep | ~30 min | System-wide optimization |
Consolidation Phases
Phase 1: Pattern Detection
Identify recurring patterns across memories:
- Similar problems solved multiple ways
- Frequently co-accessed memories
- Successful strategies repeated
Phase 2: Schema Formation
Create higher-level abstractions:
- "When X happens, Y usually works"
- Merge similar memories into schemas
- Reduce redundancy
Phase 3: Conflict Resolution
Detect and resolve contradictions:
- Same problem, different solutions stored
- Outdated information conflicting with new
- Decide which to keep based on recency + success
Phase 4: Temporal Decay
Apply time-based forgetting:
- Unused memories decay in Q-value
- Very old, never-accessed memories pruned
- Keep core knowledge stable
Phase 5: Cross-Context Transfer
Share useful patterns between contexts:
- Debugging insight useful for coding
- Research finding applicable to implementation
- Generalize specific solutions
Phase 6: QAVR Sync
Update Q-value rankings based on consolidation:
- Boost patterns with high success
- Demote patterns that didn't work
- Rebalance context weights
Output Report
## Memory Consolidation Report
**Date**: [timestamp]
**Type**: [Light/Standard/Deep]
**Duration**: [X minutes]
### Health Metrics
- Total memories: X
- Active (accessed 30d): X
- Dormant (no access 30d): X
- Conflicts detected: X
- Patterns identified: X
### Actions Taken
- Memories merged: X
- Memories pruned: X
- Schemas created: X
- Conflicts resolved: X
- Cross-context transfers: X
### Top Patterns Identified
1. [pattern description]
2. [pattern description]
3. [pattern description]
### Recommendations
- [suggestion for improvement]
### System Health Score
[X/100]
Usage
Manual Invocation
/memory-consolidation daily # Quick health check
/memory-consolidation weekly # Standard consolidation
/memory-consolidation monthly # Deep optimization
Automated Scheduling
Configure in clawdbot.json:
{
"memory": {
"consolidation": {
"daily": "03:00",
"weekly": "sunday 04:00",
"monthly": "1st 05:00"
}
}
}
Benefits
- Reduced Noise: Old, unhelpful memories pruned
- Better Retrieval: Patterns surface useful info
- Conflict-Free: No contradictory advice
- Cross-Pollination: Insights shared across domains
- Efficiency: Less storage, faster queries
