Agent skill · data analytics · aiskillstore
azure-ai-anomalydetector-java
Build anomaly detection applications with Azure AI Anomaly Detector SDK for Java. Use when implementing univariate/multivariate anomaly detection, time-series analysis, or AI-powered monitoring.
Why this skill is useful
Provides specific Java SDK commands and patterns for implementing anomaly detection that the AI wouldn't reliably generate on its own.
What it needs
Requires maven installed locally. Requires azure account access. About 3k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
Azure AI Anomaly Detector SDK for Java Build anomaly detection applications using the Azure AI Anomaly Detector SDK for Java. Installation Client Creation Sync and Async Clients With DefaultAzureCredential Key Concepts Univariate Anomaly Detection Batch Detection: Analyze entire time series at once Streaming Detection: Real-time detection on latest data point Change Point Detection: Detect trend changes in time series Multivariate Anomaly Detection Detect anomalies across 300+ correlated signals Uses Graph Attention Network for inter-correlations Three-step process: Train → Inference → Results Core Patterns Univariate Batch Detection Univariate Last Point Detection (Streaming) Change Point Detection Multivariate Model Training Multivariate Batch Inference Multivariate Last Point Detection Model Management Error Handling Environment Variables Best Practices 1. Minimum Data Points: Univariate requires at least 12 points; more data improves accuracy 2. Granularity Alignment: Match TimeGranularity to your actual data frequency 3. Sensitivity Tuning: Higher values (0-99) detect more anomalies 4. Multivariate Training: Use 200-1000 sliding window based on pattern complexity 5. Error Handling: Always handle HttpResponseException for API errors Trigger Phrases "anomaly detection Java" "detect anomalies time series" "multivariate anomaly Java" "univariate anomaly detection" "streaming anomaly detection" "change point detection" "Azure AI Anomaly Detector" When to Use This skill is applicable to execute the workflow or actions described in the overview. Limitations Use this skill only when the task clearly matches the scope described above. Do not treat the output as a substitute for environment-specific validation, testing, or expert review. Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/azure-ai-anomalydetector-java