System Monitor: Hardware & Performance Dashboard

Keep your Mac mini running optimally with the System Monitor skill. Track CPU usage, memory pressure, storage availability, and network throughput in real-time. Get AI-powered insights and recommendations for performance optimization, and receive alerts before issues become critical.

Features

• Real-time metrics dashboard - Monitor all vital system metrics at a glance
• Historical performance data - Track trends and identify patterns over time
• AI anomaly detection - Automatically identify unusual behavior before it becomes a problem
• Predictive alerts - Get notified before resource exhaustion occurs
• Resource optimization suggestions - AI-powered recommendations for better performance
• Export reports - Generate detailed reports for analysis
• Custom alert thresholds - Set personalized limits for each metric
• Multi-source data aggregation - Correlate metrics from different system sources

Hero Stats

• ⭐ 4.7/5 rating based on 8,400+ downloads
• 🚀 Average response time: <100ms for metric queries
• 📊 Data retention: Up to 90 days of historical data
• 💾 Storage overhead: <500MB for full metrics database
• 🔔 Alert accuracy: 98.5% true positive rate

Quick Install

# Install System Monitor skill
clawdbot skills install system-monitor

# Start monitoring immediately
clawdbot monitor start

# Configure alert thresholds
clawdbot monitor alerts set cpu 90
clawdbot monitor alerts set memory 85
clawdbot monitor alerts set disk 90

# View real-time metrics dashboard
clawdbot monitor dashboard

# Enable AI anomaly detection
clawdbot monitor ai enable

Prerequisites

• OpenClaw core service running
• Admin access for system metrics (sudo privileges)
• At least 500MB free disk space for metrics storage
• macOS 15.0 or later for full sensor support

Running on Mac Mini M4

The Mac mini M4 is the ideal hardware platform for System Monitor, offering significant advantages over cloud-based or remote monitoring solutions:

Why Local Hardware Matters

Ultra-Low Latency Monitoring

• Metric collection at 1-second intervals without network overhead
• Instant alerts when thresholds are breached
• Real-time visualization without API polling delays

24/7 Reliability

• Mac mini M4 consumes only 5-10W in idle mode
• Runs continuously for <$15/year in electricity costs
• No network dependency means monitoring works even during internet outages

Hardware-Accurate Metrics

• Direct access to M4 chip sensors (temperature, power states)
• Native integration with macOS power management
• Accurate memory pressure readings from unified memory architecture

Privacy & Security

• All system data stays on your local machine
• No telemetry or metrics sent to external servers
• Full control over data retention and access

Cost Efficiency

• No monthly subscription fees for monitoring services
• No API call costs for metric queries
• One-time hardware investment with years of service

Configuration

Essential Environment Variables

Environment Variable	Description	Default Value	Example
MONITOR sampling_interval	Time between metric collection cycles (seconds)	5	clawdbot monitor config set sampling-interval 5
MONITOR retention_days	Days to keep historical metrics before cleanup	30	clawdbot monitor config set retention-days 90
MONITOR log_level	Verbosity of monitoring logs (debug, info, warn, error)	info	clawdbot monitor config set log-level debug
MONITOR alert_cooldown	Minimum seconds between alert notifications	300	clawdbot monitor config set alert-cooldown 600
MONITOR notification_channel	Where to send alerts (console, email, slack, webhook)	console	clawdbot monitor config set notification-channel slack
MONITOR disk_path	Specific disk mount point to monitor	/	clawdbot monitor config set disk-path /Volumes/Data

Advanced Configuration

# Custom monitoring configuration
clawdbot monitor config set sampling-interval 5
clawdbot monitor config set retention-days 30
clawdbot monitor config set notifications slack
clawdbot monitor config set webhook-url https://hooks.slack.com/services/YOUR/WEBHOOK/URL

# Export metrics for external analysis
clawdbot monitor export --format json --output ./metrics.json
clawdbot monitor export --format csv --output ./metrics.csv

# Set up custom alert rules
clawdbot monitor alerts create --name "HighCPU" --metric cpu --threshold 85 --duration 300
clawdbot monitor alerts create --name "LowMemory" --metric memory --threshold 10 --duration 60

Real-World Use Cases

1. Personal Productivity: Preventing Slowdowns During Work

The Problem: Your Mac mini becomes unresponsive during critical work hours because of runaway processes or memory leaks, causing lost productivity.

The Solution: System Monitor detects performance degradation before it impacts your work and automatically takes corrective action.

# Set up proactive monitoring for work hours (9 AM - 6 PM)
clawdbot monitor alerts create \
  --name "WorkHoursPerformance" \
  --metric cpu \
  --threshold 80 \
  --action notify \
  --schedule "weekdays 09:00-18:00"

# Configure automatic restart of problematic services
clawdbot monitor automation create \
  --trigger "memory-pressure > 90%" \
  --action "restart-browser" \
  --description "Restart browser when memory is critical"

Outcome: System Monitor identified a memory leak in your web browser that was consuming 8GB over 4 hours. It automatically closed the problematic tab and sent you a notification, preventing a system freeze during an important video call.

2. Developer/Technical: Debugging Performance Issues in Development

The Problem: As a developer, you need to understand how your applications impact system resources, identify bottlenecks, and optimize performance before deployment.

The Solution: Use System Monitor's detailed metrics and AI insights to correlate application behavior with system performance.

# Start monitoring before launching your development server
clawdbot monitor start

# Tag metrics for a specific session
clawdbot monitor tag start --session "api-v2-testing"

# Run your load tests or development workflow
# ... your work here ...

# Stop monitoring and generate report
clawdbot monitor tag stop --session "api-v2-testing"
clawdbot monitor report --session "api-v2-testing" --output ./perf-report.md

# Export metrics for analysis in Python/R/Excel
clawdbot monitor export --format json --output dev-session.json

Outcome: While testing a new API endpoint, System Monitor revealed that your code caused sustained 95% CPU usage due to an inefficient database query. The AI suggested adding an index, which reduced query time from 2.3s to 45ms and CPU usage to 12%.

3. Always-On Automation: 24/7 Home Server Health Monitoring

The Problem: Your Mac mini runs critical services 24/7 (HomeKit server, media center, file backups), but you can't manually check if services are healthy or if the system is about to run out of disk space.

The Solution: Configure System Monitor to run continuously with intelligent alerts that notify you only when human intervention is needed.

# Configure 24/7 monitoring with smart alerts
clawdbot monitor config set sampling-interval 60
clawdbot monitor config set retention-days 90
clawdbot monitor config set notification-channel slack

# Critical alerts that require immediate action
clawdbot monitor alerts set cpu 95
clawdbot monitor alerts set memory 95
clawdbot monitor alerts set disk 95

# Warning alerts for proactive management
clawdbot monitor alerts create --name "DiskSpaceWarning" --metric disk --threshold 80 --action notify
clawdbot monitor alerts create --name "TempWarning" --metric temperature --threshold 80 --action notify

# Automated cleanup actions
clawdbot monitor automation create \
  --trigger "disk-usage > 85%" \
  --action "run-cleanup-script" \
  --script-path ~/scripts/disk-cleanup.sh

# Weekly health report
clawdbot monitor schedule report --frequency weekly --day monday --time 09:00

Outcome: System Monitor detected that your Plex media server was filling the SSD with transcoder cache at 2GB per day. It automatically cleared old cache files when disk usage hit 85%, preventing server downtime. You only received a weekly summary report showing 99.7% uptime over the past month.

Advanced Features

AI Anomaly Detection

System Monitor uses machine learning to learn your Mac's normal behavior patterns and identify anomalies:

# Enable AI anomaly detection
clawdbot monitor ai enable

# Train the model (runs for 7 days to establish baseline)
clawdbot monitor ai train --duration 7d

# View anomaly insights
clawdbot monitor ai insights

# Configure anomaly sensitivity (0.0-1.0, lower = more sensitive)
clawdbot monitor ai sensitivity set 0.7

Performance Optimization Suggestions

The AI analyzes your metrics and provides actionable recommendations:

# View optimization suggestions
clawdbot monitor suggestions

# Example output:
# Suggestion 1: Your average memory usage is 82%. Consider upgrading from 16GB to 32GB RAM.
# Suggestion 2: /usr/sbin/kernel_task consumes 15% CPU when temperature > 80°C. Improve case ventilation.
# Suggestion 3: SSD writes are 3x higher than reads. Consider moving /tmp to RAM disk.

Troubleshooting

Common Issues

Issue: Monitor service won't start

# Check if another monitoring tool is running (iStatMenus, Stats, etc.)
# Disable conflicting tools
sudo killall iStatMenus

# Restart System Monitor
clawdbot monitor restart

Issue: Inaccurate CPU readings

# Reset metrics database
clawdbot monitor reset --force

# Recalibrate sensors
clawdbot monitor calibrate

Issue: Alerts not firing

# Check alert configuration
clawdbot monitor alerts list

# Test alert system
clawdbot monitor alerts test --name "HighCPU"

# Verify notification channel
clawdbot monitor config test-notification

Performance Tips

1. Optimize Sampling Interval

   • Production servers: 60-300 seconds
   • Development machines: 5-15 seconds
   • Debugging issues: 1-5 seconds

2. Manage Storage

   • Keep retention at 30 days for normal use
   • Increase to 90 days for trend analysis
   • Export old data instead of keeping it in the database

3. Alert Strategy

   • Set critical thresholds at 90-95%
   • Set warning thresholds at 75-85%
   • Use cooldown periods to prevent alert fatigue

Documentation

Full documentation available at: /docs/skills/system-monitor

Repository

https://github.com/clawdbot/skills/tree/main/system-monitor

Changelog

Version 1.2.0 (Latest)

• Added M4 chip temperature monitoring
• Improved AI anomaly detection accuracy by 23%
• New automated cleanup actions
• Slack and webhook notification support

Version 1.1.0

• Historical data export in JSON/CSV formats
• Custom alert rules with duration-based triggers
• Weekly health report scheduling

Version 1.0.0

• Initial release with real-time monitoring
• CPU, memory, disk, and network metrics
• Basic alert system