Azure AI Personalizer Skill

This skill provides expert guidance for Azure AI Personalizer. Covers troubleshooting, decision making, limits & quotas, 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

Category	Lines	Description
Troubleshooting	L34-L38	Diagnosing and resolving common Azure Personalizer issues, including configuration, learning behavior, low-quality recommendations, API errors, and integration or data/feature problems.
Decision Making	L39-L43	Guidance on when to use single-slot vs multi-slot Personalizer, comparing scenarios, behavior, and design tradeoffs for different personalization needs.
Limits & Quotas	L44-L48	Guidance on scaling Personalizer for high-traffic workloads, capacity planning, throughput/latency expectations, and performance considerations under Azure limits and quotas.
Security	L49-L54	Configuring encryption at rest (including customer-managed keys) and controlling data collection, storage, and privacy settings for Azure Personalizer.
Configuration	L55-L64	Configuring Personalizer’s learning behavior: policies, hyperparameters, exploration, apprentice mode, explainability, model export, and learning loop settings.
Integrations & Coding Patterns	L65-L68	Using the Personalizer local inference SDK for low-latency, offline/edge scenarios, including setup, integration patterns, and best practices for calling the model locally.

Troubleshooting

Topic	URL
Troubleshoot common Azure Personalizer issues	https://learn.microsoft.com/en-us/azure/ai-services/personalizer/frequently-asked-questions

Decision Making

Topic	URL
Choose between single-slot and multi-slot Personalizer	https://learn.microsoft.com/en-us/azure/ai-services/personalizer/concept-multi-slot-personalization

Limits & Quotas

Topic	URL
Plan scalability and performance for Personalizer workloads	https://learn.microsoft.com/en-us/azure/ai-services/personalizer/concepts-scalability-performance

Security

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

Configuration

Topic	URL
Configure learning policy and hyperparameters in Personalizer	https://learn.microsoft.com/en-us/azure/ai-services/personalizer/concept-active-learning
Configure exploration settings for Azure Personalizer	https://learn.microsoft.com/en-us/azure/ai-services/personalizer/concepts-exploration
Enable and use inference explainability in Personalizer	https://learn.microsoft.com/en-us/azure/ai-services/personalizer/how-to-inference-explainability
Configure apprentice mode learning behavior in Personalizer	https://learn.microsoft.com/en-us/azure/ai-services/personalizer/how-to-learning-behavior
Export and manage Personalizer model and learning settings	https://learn.microsoft.com/en-us/azure/ai-services/personalizer/how-to-manage-model
Configure Azure Personalizer learning loop settings	https://learn.microsoft.com/en-us/azure/ai-services/personalizer/how-to-settings

Integrations & Coding Patterns

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