| name | slm-status |
| description | Check SuperLocalMemory system status, health, and statistics. Use when the user wants to know memory count, graph stats, patterns learned, database health, or system diagnostics. Shows comprehensive system health dashboard. |
| version | 3.4.23 |
| license | AGPL-3.0-or-later |
| compatibility | Requires SuperLocalMemory V2 installed at ~/.claude-memory/ |
| attribution | {"creator":"Varun Pratap Bhardwaj","role":"Solution Architect & Original Creator","project":"SuperLocalMemory V2"} |
SuperLocalMemory: Status
Check system status, health metrics, and statistics for your local memory system.
Usage
slm status [--verbose] [--check-integrity]
Example Output
Basic Status
$ slm status
Output:
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ā SuperLocalMemory V2 - System Status ā
āāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāā
š Memory Statistics
Total Memories: 1,247
This Month: 143
This Week: 28
Today: 5
š Knowledge Graph
Nodes (Entities): 892
Edges (Relationships): 3,456
Clusters: 47
Avg Cluster Size: 19 memories
šÆ Pattern Learning
Coding Patterns: 34
Framework Preferences: React (72%), Vue (18%), Angular (10%)
Testing Style: TDD (65%), BDD (35%)
Performance Priority: High (78%)
š¾ Database Health
Size: 4.2 MB
Integrity: ā
OK
Last Backup: 2026-02-07 09:15
Backup Count: 12
š§ Current Profile
Name: default
Created: 2026-01-15
Last Used: 2026-02-07 14:23
āļø System Info
Install Path: ~/.claude-memory
Database: memory.db
Python Version: 3.11.7
SQLite Version: 3.43.2
ā
Status: HEALTHY
Verbose Mode
$ slm status --verbose
Additional information:
- Recent memory IDs
- Top entities in graph
- Pattern confidence scores
- Database table sizes
- Index statistics
Integrity Check
$ slm status --check-integrity
Runs full database integrity check:
Running integrity check...
Database Structure: ā
OK
FTS5 Index: ā
OK
Graph Consistency: ā
OK
Orphaned Nodes: 0 found
Duplicate Memories: 0 found
Corrupted Entries: 0 found
ā
All checks passed
What This Shows
1. Memory Statistics
- Total: All memories ever saved
- This Month: Memories added in current month
- This Week: Last 7 days
- Today: Memories added today
Useful for:
- Understanding usage patterns
- Tracking growth
- Identifying active periods
2. Knowledge Graph
- Nodes: Unique entities extracted (people, technologies, concepts)
- Edges: Relationships between entities
- Clusters: Auto-discovered topic groups
- Avg Cluster Size: Memories per cluster
Health indicators:
- High edges/nodes ratio = well-connected knowledge
- Many clusters = diverse topics
- Large clusters = focused work
3. Pattern Learning
- Coding Patterns: Identified preferences and decisions
- Framework Preferences: Usage distribution
- Testing Style: TDD vs BDD preference
- Performance Priority: How important performance is to you
Based on:
- Keywords in memories ("prefer", "use", "avoid")
- Frequency of mentions
- Importance levels
- Recency (recent patterns weighted higher)
4. Database Health
- Size: Database file size
- Integrity: PRAGMA integrity_check result
- Last Backup: Most recent backup timestamp
- Backup Count: Total backups available
Warning signs:
- ā Integrity: NOT OK ā Database corrupted
- ā ļø Size > 100MB ā Consider archiving old memories
- ā ļø No backups ā Enable backup system
5. Current Profile
- Name: Active profile (default, work, personal, etc.)
- Created: When profile was created
- Last Used: Last access timestamp
Profiles allow:
- Profile isolation
- Context switching
- Separate memory spaces
6. System Info
- Install Path: Where SuperLocalMemory is installed
- Database: Database filename
- Python Version: Python interpreter version
- SQLite Version: SQLite engine version
Options
| Option | Description | Use Case |
|---|
--verbose | Show detailed stats | Debugging, analysis |
--check-integrity | Run full DB check | Troubleshooting |
--format json | JSON output | Scripting |
--format text | Human-readable (default) | Terminal use |
Use Cases
1. Health Check Before Important Work
slm status --check-integrity
2. Understanding Memory Usage
slm status
3. Performance Monitoring
slm status --verbose
4. Backup Verification
slm status | grep "Last Backup"
5. Profile Switching Context
slm status
slm switch-profile personal
slm status
Advanced Usage
Scripting & Automation
Daily health check (cron job):
#!/bin/bash
status=$(slm status --check-integrity)
if echo "$status" | grep -q "NOT OK"; then
echo "SuperLocalMemory: Integrity check FAILED" | mail -s "Alert" you@example.com
fi
Monitoring script:
#!/bin/bash
count=$(slm status | grep "Total Memories:" | awk '{print $3}' | tr -d ',')
echo "$(date),${count}" >> memory-growth.csv
JSON output for dashboards:
slm status --format json > status.json
Performance Indicators
Good indicators:
- Graph nodes > 100 ā Rich knowledge base
- Edges/nodes ratio > 2 ā Well-connected
- Patterns learned > 10 ā AI understands your style
- Integrity: OK ā Database healthy
Warning signs:
- Database size > 50MB but <100 memories ā Possible issue
- Backup count: 0 ā No disaster recovery
- Last used: >30 days ago ā Stale data
Troubleshooting
"Status command hangs"
Cause: Database locked by another process
Solution:
lsof ~/.claude-memory/memory.db
killall python3
slm status
"Integrity check fails"
Cause: Database corruption
Solution:
cp ~/.claude-memory/backups/memory.db.backup.* ~/.claude-memory/memory.db
slm status --check-integrity
"Pattern stats missing"
Cause: Need more memories (minimum 20)
Solution:
slm status | grep "Total Memories"
slm remember "Prefer React hooks over classes"
slm build-graph
Output Interpretation
Status: HEALTHY
ā
All systems operational
- Database intact
- Graph built
- Patterns learned
- Backups available
Status: WARNING
ā ļø Minor issues detected
- Old backups
- Large database
- Few patterns learned
Action: Review verbose output
Status: ERROR
ā Critical issues
- Database corrupted
- Integrity check failed
- No accessible data
Action: Restore from backup immediately
Performance Benchmarks
| Command | Typical Time | Notes |
|---|
slm status | ~200ms | Fast, lightweight |
slm status --verbose | ~500ms | More data fetching |
slm status --check-integrity | ~2s | Full DB scan |
For large databases (10,000+ memories):
- Basic status: ~500ms
- Verbose: ~1.5s
- Integrity check: ~10s
Notes
- Non-destructive: Status check never modifies data
- Real-time: Shows current state (not cached)
- Cross-tool: Same status from all AI tools
- Privacy: All checks local, no external calls
Related Commands
slm list - List recent memories
slm build-graph - Rebuild knowledge graph
slm switch-profile - Switch memory profile
slm recall - Search memories
Created by: Varun Pratap Bhardwaj (Solution Architect)
Project: SuperLocalMemory V2
License: MIT (see LICENSE)
Repository: https://github.com/varun369/SuperLocalMemoryV2
Open source doesn't mean removing credit. Attribution must be preserved per MIT License terms.