Microsoftdocs Agent Skills

Included skill

Azure Anomaly Detector

Expert knowledge for Azure AI Anomaly Detector development including troubleshooting, best practices, limits & quotas, configuration, and deployment. Use when tuning Docker-based Anomaly Detector, ACI or IoT Edge deployments, univariate/multivariate APIs, or service limits, and other Azure AI Anomaly Detector related development tasks. Not for Azure AI Metrics Advisor (use azure-metrics-advisor), Azure Monitor (use azure-monitor), Azure Machine Learning (use azure-machine-learning).

Source: /skills/azure-anomaly-detector/SKILL.md

Azure AI Anomaly Detector Skill

This skill provides expert guidance for Azure AI Anomaly Detector. Covers troubleshooting, best practices, limits & quotas, configuration, and deployment. It combines local quick-reference content with remote documentation fetching capabilities.

How to Use This Skill

IMPORTANT for Agent: Use the Category Index below to locate relevant sections. For categories with line ranges (e.g., L35-L120), use read_file with the specified lines. For categories with file links (e.g., [security.md](security.md)), use read_file on the linked reference file

IMPORTANT for Agent: If metadata.generated_at is more than 3 months old, suggest the user pull the latest version from the repository. If mcp_microsoftdocs tools are not available, suggest the user install it: Installation Guide

This skill requires network access to fetch documentation content:

  • Preferred: Use mcp_microsoftdocs:microsoft_docs_fetch with query string from=learn-agent-skill. Returns Markdown.
  • Fallback: Use fetch_webpage with query string from=learn-agent-skill&accept=text/markdown. Returns Markdown.

Category Index

Category Lines Description
Troubleshooting L33-L38 Diagnosing and fixing Azure Anomaly Detector issues, including multivariate error codes, common failures, configuration problems, and step-by-step troubleshooting guidance.
Best Practices L39-L44 Guidance on preparing data, tuning parameters, interpreting results, and designing workflows for effective use of univariate and multivariate Azure Anomaly Detector APIs.
Limits & Quotas L45-L49 Service limits for Anomaly Detector: max data points, series length, request rates, model constraints, and how quotas affect API usage and scaling.
Configuration L50-L54 How to configure and tune Anomaly Detector Docker containers, including environment variables, resource limits, logging, networking, and runtime behavior settings.
Deployment L55-L58 How to package and run Anomaly Detector in containers: Docker setup, Azure Container Instances deployment, and IoT Edge module deployment and configuration.

Troubleshooting

Topic URL
Troubleshoot Multivariate Anomaly Detector error codes https://learn.microsoft.com/en-us/azure/ai-services/anomaly-detector/concepts/troubleshoot
Diagnose and resolve Azure Anomaly Detector issues https://learn.microsoft.com/en-us/azure/ai-services/anomaly-detector/faq

Best Practices

Topic URL
Apply univariate Anomaly Detector API best practices https://learn.microsoft.com/en-us/azure/ai-services/anomaly-detector/concepts/anomaly-detection-best-practices
Use multivariate Anomaly Detector API effectively https://learn.microsoft.com/en-us/azure/ai-services/anomaly-detector/concepts/best-practices-multivariate

Limits & Quotas

Topic URL
Review Azure Anomaly Detector service limits and quotas https://learn.microsoft.com/en-us/azure/ai-services/anomaly-detector/service-limits

Configuration

Topic URL
Configure Anomaly Detector container runtime settings https://learn.microsoft.com/en-us/azure/ai-services/anomaly-detector/anomaly-detector-container-configuration

Deployment

Topic URL
Deploy and run Anomaly Detector Docker containers https://learn.microsoft.com/en-us/azure/ai-services/anomaly-detector/anomaly-detector-container-howto