ML-based anomaly detection and model training for vibration signals using the predictive-maintenance-mcp server. Use this skill when the user says "anomaly detection", "train model", "detect anomalies", "outlier detection", "normal vs abnormal", "machine learning", "one-class SVM", "LOF", "local outlier factor", "train anomaly model", "predict anomalies", "PCA visualization", "clustering", or wants to build or use anomaly detection models on vibration data.
How to install anomaly-detection?
lgdimaggio/predictive-maintenance-mcp/anomaly-detection
$npx -y skills add lgdimaggio/predictive-maintenance-mcp --skill anomaly-detectionInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/lgdimaggio/predictive-maintenance-mcp" --skill "lgdimaggio/predictive-maintenance-mcp/anomaly-detection"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/lgdimaggio/predictive-maintenance-mcp" that are relevant to the current task. Run `npx skills add "https://github.com/lgdimaggio/predictive-maintenance-mcp"` and select the relevant skills, then follow their instructions.
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