# Anomaly Detection

> Implement anomaly detection systems for outlier identification

- Skill: `lgrappag/anomaly-detection` (Agent Skill)
- Install (CLI): `npx skillmds@latest add lgrappag/anomaly-detection`
- Raw SKILL.md: https://api.skillmd.com/api/skills/lgrappag/anomaly-detection/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: LgrappaG (https://skillmd.com/u/lgrappag)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/lgrappag/anomaly-detection

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# Anomaly Detection

Implement anomaly detection systems for outlier identification

## Risk Level
**HIGH**

## Core Rules
- Calibrate thresholds
- validate detection
- test edge cases

## Response Pattern

### When Using This Skill
1. Configure detection
2. tune thresholds
3. validate results
4. Ensure performance meets requirements

## Usage Contexts
- Outlier detection
- fraud detection

## What NOT to Do
- False positives
- false negatives
- poor threshold selection

## Key Requirements
- Understand the use cases before application
- Follow the documented response pattern
- Validate results in the target environment
- Monitor for performance impact

## Further Learning
Review related skills and documentation for deeper understanding of related systems and best practices.