← 返回
未分类 中文

Claw Reliability

Agent observability — monitors tool invocations, LLM calls, token usage, costs, and anomalies with pluggable alerts and a real-time dashboard.
代理可观测性——监控工具调用、LLM调用、令牌使用量、成本和异常,支持可插拔的告警和实时仪表盘。
fiddyrod fiddyrod 来源
未分类 clawhub v1.0.6 1 版本 100000 Key: 无需
★ 0
Stars
📥 458
下载
💾 2
安装
1
版本
#latest

概述

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

版本历史

共 1 个版本

  • v1.0.6 当前
    2026-05-03 07:33 安全 安全

安全检测

腾讯云安全 (Keen)

安全,无风险
查看报告

腾讯云安全 (Sanbu)

安全,无风险
查看报告

🔗 相关推荐

ai-agent

Agent Browser

rez0
用于 AI 代理的浏览器自动化 CLI。当用户需要与网站交互(包括浏览页面、填写表单、点击按钮、截图等)时使用。
★ 865 📥 344,959
ai-agent

Self-Improving + Proactive Agent

ivangdavila
自我反思+自我批评+自我学习+自组织记忆。智能体评估自身工作、发现错误并持续改进。
★ 1,441 📥 328,500
ai-agent

self-improving agent

pskoett
记录自身发现以实现自我改进的技能
★ 4,164 📥 936,255