OpenClaw Memory
Management Guide
Master OpenClaw's memory system: MEMORY.md files, daily logs, context retention, and advanced memory management techniques.
Types of Memory in OpenClaw
Understanding the different memory layers in your OpenClaw agent
Working Memory
Session-basedTemporary context during conversations
Capacity: ~8,000 tokens
Features:
- •Current conversation context
- •Recent tool outputs
- •Active task information
- •Immediate user preferences
Management:
- ▸Automatically managed by OpenClaw
- ▸Cleared when session ends
- ▸Limited by token window
- ▸Focus on current interaction
Daily Memory
24 hoursDaily activity logs and summaries
Capacity: Unlimited file size
Features:
- •Raw interaction logs
- •Task completion records
- •Error logs and debugging info
- •Performance metrics
Management:
- ▸Stored in memory/YYYY-MM-DD.md
- ▸Automatically created daily
- ▸Includes timestamps
- ▸Searchable content
Long-term Memory
PersistentCurated knowledge and experiences
Capacity: Unlimited
Features:
- •Important facts and preferences
- •Learned behaviors and patterns
- •Project context and history
- •Key relationships and contacts
Management:
- ▸Stored in MEMORY.md
- ▸Manually curated
- ▸Structured content
- ▸Cross-referenced
Skill Memory
Persistent per skillSkill-specific knowledge and context
Capacity: Varies by skill
Features:
- •Skill configuration
- •Learning history
- •Custom parameters
- •Performance data
Management:
- ▸Stored in skill directories
- ▸Managed by skill framework
- ▸Version controlled
- ▸Exportable/importable
Memory File Structure
How OpenClaw organizes and stores memory data
MEMORY.md
Central long-term memory repository
Structure:
# MEMORY.md ## Core Facts - User: Blue Canvas, Blue Canvas AI consultancy - Location: Derry, Northern Ireland - Timezone: GMT/BST - Primary goals: Business growth, automation ## Projects ### Active Projects - Blue Canvas website optimization - UK Trade Jobs expansion - SEO automation workflows ### Completed Projects - OpenClaw Consultant launch - ClawRoster development - Client showcase system ## Preferences & Patterns - Communication style: Direct, informal - Work hours: 9am-6pm GMT - Preferred tools: OpenClaw, Vercel, Ahrefs - Automation focus: SEO, content, lead generation ## Key Relationships - Stacey (partner) - Regular clients and contacts ## Learning & Insights - What works: Practical, actionable advice - What doesn't: Generic recommendations - Important lessons learned
Maintenance Tips:
- • Update weekly with key insights
- • Remove outdated information
- • Reorganize sections as needed
- • Cross-reference with daily logs
memory/
Daily activity logs directory
Structure:
memory/ ├── 2026-03-26.md # Today's logs ├── 2026-03-25.md # Yesterday's logs ├── 2026-03-24.md # Previous day └── archives/ # Older logs (optional)
Automation Features:
- • Auto-generated from agent activities
- • Timestamped entries
- • Categorized by type
- • Searchable format
Memory Commands
Essential CLI commands for managing OpenClaw memory
Memory Reading
openclaw memory search "keyword"
Search all memory files for specific content
Example:
openclaw memory search "client onboarding"
Output:
Returns matching entries with file locations
openclaw memory get YYYY-MM-DD
Retrieve specific daily memory file
Example:
openclaw memory get 2026-03-26
Output:
Contents of the specified daily log
openclaw memory recent --days 7
Get recent memory entries
Example:
openclaw memory recent --days 3
Output:
Last 3 days of memory entries
openclaw memory summary
Get overview of memory usage and stats
Example:
openclaw memory summary
Output:
Memory size, file count, recent activity
Memory Writing
openclaw memory log "entry"
Add entry to today's memory log
Example:
openclaw memory log "Completed client project X"
Output:
Entry added with timestamp
openclaw memory note --long-term "fact"
Add important fact to MEMORY.md
Example:
openclaw memory note --long-term "User prefers morning meetings"
Output:
Fact added to appropriate section
openclaw memory update-context
Update memory context from recent activities
Example:
openclaw memory update-context
Output:
Memory files updated with recent context
Memory Management
openclaw memory clean --days 30
Archive old memory files
Example:
openclaw memory clean --days 30
Output:
Files older than 30 days archived
openclaw memory distill
Extract key insights from daily logs to MEMORY.md
Example:
openclaw memory distill --week
Output:
Weekly insights added to long-term memory
openclaw memory export
Export memory for backup or analysis
Example:
openclaw memory export --format json
Output:
Memory data exported to specified format
Memory Strategies
Advanced techniques for optimizing your agent's memory
Hierarchical Memory
Organize memory by importance and frequency
Implementation:
- •Store frequently accessed info in MEMORY.md
- •Keep detailed logs in daily files
- •Archive old information periodically
- •Cross-reference between layers
Benefits:
- ✓Faster information retrieval
- ✓Better context preservation
- ✓Reduced memory overhead
- ✓Improved agent performance
Contextual Tagging
Tag memory entries with relevant context
Implementation:
- •Use consistent hashtags (#project, #client)
- •Add category markers ([TASK], [INSIGHT])
- •Include relationship indicators (@person)
- •Apply priority levels (HIGH, MEDIUM, LOW)
Benefits:
- ✓Enhanced searchability
- ✓Better organization
- ✓Improved recall accuracy
- ✓Context-aware responses
Memory Consolidation
Regularly merge and refine memory content
Implementation:
- •Weekly review of daily logs
- •Extract key patterns and insights
- •Update MEMORY.md with important facts
- •Remove outdated information
Benefits:
- ✓Reduced information overload
- ✓Improved memory quality
- ✓Better long-term retention
- ✓More relevant context
Associative Memory
Link related memories for better recall
Implementation:
- •Create cross-references between entries
- •Link related projects and tasks
- •Connect people with their preferences
- •Associate outcomes with methods
Benefits:
- ✓Enhanced understanding
- ✓Better pattern recognition
- ✓Improved decision making
- ✓Contextual awareness
Automated Memory Workflows
Set up automated memory management workflows
Daily Memory Processing
0 23 * * *Automated daily memory management
Workflow Actions:
- 1.Extract key events from today's activities
- 2.Categorize and tag important entries
- 3.Update relevant sections in MEMORY.md
- 4.Clean up and organize daily log
- 5.Prepare summary for tomorrow's context
Configuration:
{
"name": "daily-memory-process",
"schedule": "0 23 * * *",
"actions": [
{
"type": "memory-extract",
"source": "today-logs",
"categories": ["tasks", "insights", "issues"]
},
{
"type": "memory-update",
"target": "MEMORY.md",
"sections": ["recent-activity", "current-projects"]
},
{
"type": "memory-clean",
"optimize": true
}
]
}Weekly Memory Consolidation
0 20 * * 0Comprehensive weekly memory review
Workflow Actions:
- 1.Review all daily logs from the past week
- 2.Identify patterns and recurring themes
- 3.Update long-term memory with insights
- 4.Archive completed projects
- 5.Plan next week's priorities
Configuration:
{
"name": "weekly-memory-review",
"schedule": "0 20 * * 0",
"actions": [
{
"type": "memory-analyze",
"timeframe": "7days",
"extract": ["patterns", "insights", "outcomes"]
},
{
"type": "memory-consolidate",
"target": "MEMORY.md",
"update-sections": ["key-insights", "project-status"]
},
{
"type": "memory-archive",
"criteria": "completed-projects"
}
]
}Context-Aware Responses
Use memory for better user interactions
Workflow Actions:
- 1.Check recent memory for relevant context
- 2.Search long-term memory for user preferences
- 3.Apply context to response generation
- 4.Log interaction for future reference
Configuration:
{
"name": "context-response",
"trigger": "user-message",
"actions": [
{
"type": "memory-search",
"query": "{{ user_message }}",
"sources": ["MEMORY.md", "recent-logs"]
},
{
"type": "context-apply",
"memory": "search-results",
"response": "enhanced"
},
{
"type": "memory-log",
"entry": "user-interaction",
"context": "response-given"
}
]
}Memory Optimization
Memory Compression
Reduce memory size while preserving key information
Methods:
- •Summarize long entries into key points
- •Remove redundant information
- •Use abbreviations for frequent terms
- •Archive old, rarely-accessed data
Selective Retention
Keep only the most relevant information
Methods:
- •Score entries by importance and frequency
- •Automatically delete low-value entries
- •Prioritize recent and relevant information
- •Maintain critical facts regardless of age
Context Prediction
Predict what information will be needed
Methods:
- •Analyze usage patterns
- •Pre-load likely-needed context
- •Cache frequently accessed information
- •Optimize memory layout for access patterns
Memory Indexing
Create efficient indexes for fast retrieval
Methods:
- •Build keyword indexes
- •Create category mappings
- •Maintain relationship graphs
- •Use timestamp-based indexing
Troubleshooting Memory Issues
Memory Files Growing Too Large
Symptoms:
- •Slow memory searches
- •Large file sizes
- •Performance degradation
Solutions:
- ✓Implement regular archiving (openclaw memory clean)
- ✓Use memory compression techniques
- ✓Split large files by time period
- ✓Remove redundant entries regularly
Context Not Being Retained
Symptoms:
- •Agent doesn't remember previous conversations
- •Repeated questions about same topics
- •Loss of user preferences
Solutions:
- ✓Check MEMORY.md is being updated
- ✓Verify memory logging is working
- ✓Review memory search functionality
- ✓Ensure proper context loading
Memory Search Not Working
Symptoms:
- •No results for known information
- •Slow search responses
- •Incorrect search results
Solutions:
- ✓Rebuild search indexes
- ✓Check file permissions
- ✓Verify search query format
- ✓Update search algorithms
Need Help with
Memory Management?
Get expert guidance on setting up efficient memory systems for your OpenClaw agents.
- ✓Memory architecture design
- ✓Optimization strategies
- ✓Performance troubleshooting
Memory Management Support
Optimize your agent's memory systems