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Iot Anomalies

ASecurity

Detect and classify telemetry anomalies on Cognitum Seed devices

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  • Added May 27, 2026
data-aibash

Works with

  • mcp

Security analysis

A100/100

Scanned May 27, 2026

npx -y skills add ruvnet/ruflo --skill iot-anomalies --agent claude-code

Installs into .claude/skills of the current project.

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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" })`

Attribution

ruvnetView sourceSee grades on GitHubMore from ruvnet

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