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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

集成工具Azure

查看安装方法

包含的文件（1）

SKILL.md4.5 KB

SKILL.md（原文）

安装前可以查看交给 AI 代理的指令内容。

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

Category	Lines	Description
Troubleshooting	L33-L37	Diagnosing 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 Making	L38-L42	Guidance on when to use single-slot vs multi-slot Personalizer, comparing scenarios, behavior, and design tradeoffs for different personalization needs.
Security	L43-L48	Configuring encryption at rest (including customer-managed keys) and controlling data collection, storage, and privacy settings for Azure Personalizer.
Configuration	L49-L55	Configuring Personalizer’s learning behavior: policies, hyperparameters, exploration, apprentice mode, explainability, model export, and learning loop settings.
Integrations & Coding Patterns	L56-L59	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 issues in Azure Personalizer	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

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
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
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

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azure-active-directory-b2c

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Expert knowledge for Azure Active Directory B2C development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building B2C user flows/custom policies, configuring IdPs/MFA, securing APIs, automating CI/CD, or monitoring with Sentinel, and other Azure Active Directory B2C related development tasks. Not for Azure Role-based access control (use azure-rbac), Azure Information Protection (use azure-information-protection), Azure Security (use azure-security), Azure Sentinel (use azure-sentinel).

中文简介正在准备中。当前显示原文说明。