iot-anomalies
Detect and classify telemetry anomalies on Cognitum Seed devices. Use when investigating a device that's reporting odd metrics, before approving a firmware canary advancement, or when triaging fleet-wide health alerts.
来源信息
- 仓库
- ruvnet/ruflo
- 最近来源活动
- 2026年7月17日 03:06
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- 英语
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安装方式
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
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SKILL.md
来源说明 · 只读预览- name
- iot-anomalies
- description
- Detect and classify telemetry anomalies on Cognitum Seed devices. Use when investigating a device that's reporting odd metrics, before approving a firmware canary advancement, or when triaging fleet-wide health alerts.
- allowed-tools
- Bash(npx *) mcp__plugin_ruflo-core_ruflo__memory_store Read
- argument-hint
- <device-id>
Run Z-score anomaly detection on a device's recent telemetry.
Steps:
1. `npx -y -p @claude-flow/plugin-iot-cognitum@latest cognitum-iot anomalies DEVICE_ID`
2. Review detected anomaly types (spike, flatline, drift, oscillation, pattern-break, cluster-outlier)
3. If score > 0.9, recommend quarantine
4. Store anomaly pattern for learning:
`mcp__plugin_ruflo-core_ruflo__memory_store({ key: "iot-anomaly-DEVICEID", value: "TYPE at SCORE", namespace: "iot-anomalies" })`
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