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azure-personalizer

Expert knowledge for Azure AI Personalizer development including troubleshooting, decision making, security, configuration, and integrations & coding patterns. Use when choosing single vs multi-slot setups, tuning policies/exploration, using apprentice mode, explainability, or local inference, and other Azure AI Personalizer related development tasks. Not for Azure AI Search (use azure-cognitive-search), Azure Machine Learning (use azure-machine-learning), Azure AI Metrics Advisor (use azure-metrics-advisor), Azure AI Anomaly Detector (use azure-anomaly-detector).

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MicrosoftDocs/Agent-Skills
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Azure AI Personalizer Skill

This skill provides expert guidance for Azure AI Personalizer. Covers troubleshooting, decision making, security, configuration, and integrations & coding patterns. 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

CategoryLinesDescription
TroubleshootingL33-L37Diagnosing and fixing common Azure Personalizer issues: API errors, event/Reward calls, model training problems, configuration mistakes, and steps to validate and debug your setup.
Decision MakingL38-L42Guidance on when to use single-slot vs multi-slot Personalizer, comparing scenarios, behavior, and design tradeoffs for different personalization needs.
SecurityL43-L48Configuring encryption at rest (including customer-managed keys) and controlling data collection, storage, and privacy settings for Azure Personalizer.
ConfigurationL49-L55Configuring Personalizer’s learning behavior: policies, hyperparameters, exploration, apprentice mode, explainability, model export, and learning loop settings.
Integrations & Coding PatternsL56-L59Using the Personalizer local inference SDK for low-latency, offline/edge scenarios, including setup, integration patterns, and best practices for calling the model locally.

Troubleshooting

TopicURL
Troubleshoot common issues in Azure Personalizerhttps://learn.microsoft.com/en-us/azure/ai-services/personalizer/frequently-asked-questions

Decision Making

TopicURL
Choose between single-slot and multi-slot Personalizerhttps://learn.microsoft.com/en-us/azure/ai-services/personalizer/concept-multi-slot-personalization

Security

TopicURL
Configure data-at-rest encryption and CMK for Personalizerhttps://learn.microsoft.com/en-us/azure/ai-services/personalizer/encrypt-data-at-rest
Manage data usage and privacy in Personalizerhttps://learn.microsoft.com/en-us/azure/ai-services/personalizer/responsible-data-and-privacy

Configuration

TopicURL
Enable and use inference explainability in Personalizerhttps://learn.microsoft.com/en-us/azure/ai-services/personalizer/how-to-inference-explainability
Configure apprentice mode learning behavior in Personalizerhttps://learn.microsoft.com/en-us/azure/ai-services/personalizer/how-to-learning-behavior
Configure Azure Personalizer learning loop settingshttps://learn.microsoft.com/en-us/azure/ai-services/personalizer/how-to-settings

Integrations & Coding Patterns

TopicURL
Use Personalizer local inference SDK for low latencyhttps://learn.microsoft.com/en-us/azure/ai-services/personalizer/how-to-thick-client

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