iot-anomalies

Pass

Detect and classify telemetry anomalies on Cognitum Seed devices

@ruvnetMIT5/5/2026

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Install Skill

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Install with CLI

Install globally (user-level):

npx skillhub install ruvnet/ruflo/iot-anomalies

Install in current project:

npx skillhub install ruvnet/ruflo/iot-anomalies --project

Suggested path: ~/.claude/skills/iot-anomalies/

SKILL.md Content

---
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" })`