What machine learning algorithms does this skill use?

The skill utilizes industry-standard algorithms such as Isolation Forest and One-Class Support Vector Machines (SVM) to identify data deviations.

Can I use this for real-time security monitoring?

Yes, it can be integrated with network logs and alerting systems to flag unusual traffic patterns that may indicate a security breach or unauthorized access.

What industries benefit most from this anomaly detection skill?

This skill is ideal for FinTech (fraud detection), Cybersecurity (threat detection), and Industrial IoT (predictive maintenance and quality control).

Is data preprocessing required before using this skill?

While the skill handles analysis, for best results, your data should be clean and properly formatted. The skill can provide guidance on necessary scaling and cleaning steps.

Anomaly Detection System

Name: Anomaly Detection System
Author: jeremylongshore

byjeremylongshore

•

883

Data Science & ML

Identifies outliers and unusual patterns in datasets using machine learning algorithms to uncover potential errors, fraud, or system deviations.

About

This skill empowers Claude to perform advanced statistical and machine learning-based anomaly detection directly within your development workflow. By leveraging the anomaly-detection-system plugin, it automatically selects and applies appropriate algorithms like Isolation Forest or One-Class SVM to pinpoint data points that deviate from established norms. It is particularly useful for security auditing, financial fraud analysis, and manufacturing quality control, providing actionable insights into data irregularities without requiring manual statistical modeling.

Key Features

Network traffic pattern analysis for detecting potential security breaches
Customizable threshold tuning to balance precision and sensitivity
Real-time identification of outliers in financial and transactional data
Automated ML algorithm selection including Isolation Forest and One-Class SVM
Manufacturing defect identification via industrial sensor data analysis
883 GitHub stars

Use Cases

Detecting fraudulent credit card transactions in large financial datasets
Analyzing IoT sensor data from production lines to flag manufacturing defects
Monitoring network logs for unusual traffic spikes that indicate a cyber attack

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jeremylongshore/claude-code-plugins-plus-skills anomaly-detection-system

For use in Claude.ai and ChatGPT

Download Skill

GitHub