Proactive Ops Monitor

Proactive operations monitoring for OpenClaw agents. Tracks token utilization, memory layer health, and generates alerts. Provides /health dashboard and auto-suggestions for open loops. Works with memory-stack-core to prevent context overflow.

Stop being reactive. This skill turns your agent into a proactive partner that warns you before problems hit and suggests next steps.

Capabilities

1. Health Dashboard

/health command or tool("proactive-ops-monitor", "health_dashboard")

Shows:

text

🛡️  OpenClaw Ops Dashboard
============================
Token Utilization:     62% (74k / 120k)
Memory Layers:
  • WAL entries:       1,234 (12KB)
  • Working buffer:    5.2KB (last 3 turns)
  • Daily logs:        7
Status:               ✅ Healthy

Alerts:
  • None

Suggestions (1):
  1. Session bridge file missing → run /init

2. Token Utilization Tracking

Estimates current context tokens (via char count / 4). Monitors continuously.

Thresholds (configurable):

• Warning: 70%
• Critical: 85%

When threshold crossed:

• Log to memory/ops-alerts.jsonl
• Include suggestion to /wrap_up or compact

3. Alerting

Alerts stored in memory/ops-alerts.jsonl:

json

{
  "timestamp": "2026-04-01T16:30:00Z",
  "level": "warning",
  "metric": "token_utilization",
  "value": 72,
  "message": "Token usage at 72%. Consider /wrap_up soon."
}

4. Proactive Suggestions

tool("proactive-ops-monitor", "suggest_next", {"limit": 3})

Scans:

• Open loops in memory/wal.jsonl (category=draft, decision)
• Recent conversation gaps
• Unfinished tasks from notes/areas/open-loops.md

Outputs suggested next actions:

json

[
  {
    "type": "open_loop",
    "content": "Build ollama binary on external machine",
    "context": "mentioned 2 days ago",
    "priority": "high"
  },
  {
    "type": "context",
    "content": "Finish integrating ToolRegistry into core agent"
  }
]

5. Auto-Suggest on Message

When configured, agent will automatically prepend a suggestion to its response if:

• Token utilization > 80%
• There are unresolved open loops
• Working buffer shows recent stalls

Configurable via proactive-ops-config.json.

Configuration

proactive-ops-config.json in workspace root:

json

{
  "alerts": {
    "token_warning": 70,
    "token_critical": 85,
    "buffer_warning_size_kb": 5000
  },
  "suggestions": {
    "enabled": true,
    "max_per_turn": 1,
    "include_open_loops": true,
    "include_context_gaps": true
  },
  "dashboard": {
    "show_suggestions": true,
    "show_alerts": true
  }
}

Integration

• memory-stack-core: reads WAL for open loops, buffer size for context estimation
• session-wrap-up-premium: monitor suggests wrap-up when utilization high
• agent-oversight: can forward alerts to oversight logs

Usage

Interactive slash commands:

• /health — show dashboard
• /utilization — show token %
• /suggest — show proactive next steps
• /alerts — show recent alerts

Tool calls:

python

tool("proactive-ops-monitor", "health_dashboard", {"format": "text"})
tool("proactive-ops-monitor", "suggest_next", {"limit": 3})

Pricing

$99/mo includes:

• Real-time monitoring
• Dashboard + alerts
• Proactive suggestions
• Priority support for ops issues

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Inspired by auto-monitor and proactive-agent-lite from ClawHub.