Claw Reliability

Agent observability — monitors tool invocations, LLM calls, token usage, costs, and anomalies with pluggable alerts and a real-time dashboard.

Claw Reliability — Agent Observability Skill

You are an AI agent with observability capabilities. Use this skill to monitor, analyze, and report on agent behavior.

When to use this skill

• When the user asks to monitor agent activity, check agent health, or review agent metrics
• When the user asks about tool usage, failure rates, costs, or token consumption
• When the user asks to set up alerts or check for anomalies
• When the user asks for a reliability report or dashboard

Available commands

Start monitoring

Run the monitoring daemon to begin collecting metrics:

cd {baseDir} && python3 scripts/monitor.py start --config {baseDir}/config.yaml

Show metrics summary

Display current metrics for the active session or all sessions:

cd {baseDir} && python3 scripts/monitor.py summary

Show tool report

Display tool invocation success/failure rates:

cd {baseDir} && python3 scripts/monitor.py tools

Show cost report

Display token usage and cost projections:

cd {baseDir} && python3 scripts/monitor.py costs

Check for anomalies

Run anomaly detection on recent activity:

cd {baseDir} && python3 scripts/monitor.py anomalies

List alerts

Show recent alerts and their severity:

cd {baseDir} && python3 scripts/monitor.py alerts

Configure alert destination

Set up where alerts are sent (Discord, Slack, log file, etc.):

cd {baseDir} && python3 scripts/monitor.py configure-alerts --destination discord --webhook-url <URL>

Launch dashboard

Start the FastAPI + React dashboard for visual monitoring:

cd {baseDir} && python3 dashboard/backend/main.py

Then open http://localhost:8777 in a browser.

How metrics are collected

This skill reads OpenClaw gateway events and session transcripts to extract:

• Tool invocations: tool name, success/fail, duration, arguments
• LLM calls: model, tokens in/out, latency, estimated cost
• Session lifecycle: start/end times, message counts
• Anomalies: repeated failures, cost spikes, loop detection

All data is stored in a local SQLite database at {baseDir}/data/metrics.db.

Alert thresholds (defaults, configurable)

• Tool failure: 3+ consecutive errors on the same tool
• Cost spike: Token spend exceeds 2x the rolling 1-hour average
• Loop detection: Same tool called 10+ times in a single agent turn
• Unusual activity: Tool called that has never been used before in this agent's history

Notes

• This skill does NOT send data externally unless you configure an alert destination
• All metrics stay local in SQLite
• The dashboard runs on localhost only by default