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[](https://versuz.dev/skills/ruvnet-ruflo-plugins-ruflo-iot-cognitum-skills-iot-anomalies)Free SKILL.md scraped from GitHub. Clone the repo or copy the file directly into your Claude Code skills directory.
npx versuz@latest install ruvnet-ruflo-plugins-ruflo-iot-cognitum-skills-iot-anomaliesgit clone https://github.com/ruvnet/ruflo.gitcp ruflo/SKILL.MD ~/.claude/skills/ruvnet-ruflo-plugins-ruflo-iot-cognitum-skills-iot-anomalies/SKILL.md---
name: iot-anomalies
description: Detect and classify telemetry anomalies on Cognitum Seed devices
allowed-tools: Bash(npx *) mcp__claude-flow__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__claude-flow__memory_store({ key: "iot-anomaly-DEVICEID", value: "TYPE at SCORE", namespace: "iot-anomalies" })`