Lingxi · Agent Health Monitor

Monitor OpenClaw Agent health, uptime, task status, and system metrics. Automatic alerts on failures, performance degradation, or unusual behavior. Includes memory management, session cleanup, and proactive self-healing.

lingxi-agent-monitor

Proactive health monitoring and self-healing for AI Agent systems built on OpenClaw.

What It Monitors

Metric	Check	Alert Threshold
Agent Uptime	Is agent alive?	Any downtime
Session Count	Active sessions	> 20 or < 1
Memory Usage	Agent memory consumption	> 80%
Task Queue	Pending/failed tasks	> 5 failed
MCP Connections	External tool connectivity	Any failure
API Latency	Tool response time	> 5 seconds
Error Rate	Tool call failure %	> 10%

Usage

Trigger Commands

text

"System health check"  → Full health scan + report
"Agent status"        → Quick status summary
"Memory check"         → Focus on memory metrics
"Task queue check"     → Focus on pending/failed tasks
"Alert me if..."      → Configure custom alert rules

Health Report Format

markdown

# Agent Health Report — YYYY-MM-DD HH:MM

## System Status
| Component | Status | Latency | Notes |
|-----------|--------|---------|-------|
| OpenClaw Gateway | ✅ Healthy | 45ms | |
| MCP Server | ✅ Connected | 120ms | |
| GitHub Integration | ✅ OK | 200ms | |
| ZeroGPU | ✅ OK | 80ms | |

## Session Overview
- Active sessions: 3
- Avg session duration: 23m
- Memory: 1.2GB / 4GB (30%)

## Recent Activity
- Tasks completed: 47
- Tasks failed: 2 (4.3%)
- Avg task duration: 1m 12s

## Alerts (if any)
- [ ] No critical alerts
- ⚠️ Warning: ZeroGPU latency > 500ms (3 occurrences)

Alert Levels

Level	Trigger	Action
🔴 Critical	Agent down, all tools failing	Immediate notification + restart attempt
🟡 Warning	Degraded performance, > 10% error rate	Scheduled notification
🔵 Info	New session, task milestone	Log only

Self-Healing Actions

When issues are detected, the agent can automatically:

1. Restart failed MCP connections
2. Clean up stale sessions (sessions idle > 2 hours)
3. Flush memory cache when usage > 80%
4. Retry failed tool calls (up to 3 attempts)
5. Switch to backup providers (e.g., GitHub API fallback)

Configuration

json

{
  "alert_channels": ["log", "notification"],
  "memory_threshold_pct": 80,
  "session_idle_timeout_min": 120,
  "max_sessions": 20,
  "error_rate_threshold_pct": 10,
  "latency_threshold_ms": 5000,
  "self_heal_enabled": true,
  "health_check_interval_min": 15
}

Cron Schedule

text

*/15 * * * * → Health check every 15 minutes
0 */2 * * *  → Deep memory cleanup every 2 hours

Installation

bash

clawhub install lingxi-agent-monitor

Integration with External Alerting

For external alerts (Slack, Discord, PagerDuty):

bash

# In your notification workflow
curl -X POST $SLACK_WEBHOOK \
  -H "Content-Type: application/json" \
  -d '{"text": "🔴 Agent Alert: $ALERT_MESSAGE"}'

Memory Management

When memory usage is high:

1. Archive completed session summaries to memory files
2. Clear intermediate computation cache
3. Merge small memory files into consolidated ones
4. Prune session history beyond retention limit

Dashboard Endpoint

If running with n8n bridge:

text

GET /agent-monitor/dashboard  → HTML dashboard with real-time status
GET /agent-monitor/metrics   → JSON metrics endpoint
GET /agent-monitor/alerts     → JSON alert history