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Azure AI Personalizer Skill

Azure AI Personalizer 技能

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.
本技能为Azure AI Personalizer提供专业指导，涵盖故障排查、决策制定、限制与配额、安全、配置以及集成与编码模式。它结合了本地快速参考内容与远程文档获取能力。

How to Use This Skill

如何使用本技能

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.
Agent 重要提示：使用下方的分类索引定位相关章节。对于带有行范围的分类（例如 
L35-L120
），使用
read_file
工具读取指定行内容。对于带有文件链接的分类（例如 
[security.md](security.md)
），使用
read_file
工具读取链接的参考文件
Agent 重要提示：如果
metadata.generated_at
的时间超过3个月，建议用户从仓库拉取最新版本。如果
mcp_microsoftdocs
工具不可用，建议用户安装该工具：安装指南
本技能需要网络访问权限来获取文档内容：
  • 推荐方式：使用
    mcp_microsoftdocs:microsoft_docs_fetch
    工具，携带查询字符串
    from=learn-agent-skill
    ，返回Markdown格式内容。
  • 备选方式：使用
    fetch_webpage
    工具，携带查询字符串
    from=learn-agent-skill&accept=text/markdown
    ，返回Markdown格式内容。

Category Index

分类索引

CategoryLinesDescription
TroubleshootingL34-L38Diagnosing and resolving common Azure Personalizer issues, including configuration, learning behavior, low-quality recommendations, API errors, and integration or data/feature problems.
Decision MakingL39-L43Guidance on when to use single-slot vs multi-slot Personalizer, comparing scenarios, behavior, and design tradeoffs for different personalization needs.
Limits & QuotasL44-L48Guidance on scaling Personalizer for high-traffic workloads, capacity planning, throughput/latency expectations, and performance considerations under Azure limits and quotas.
SecurityL49-L54Configuring encryption at rest (including customer-managed keys) and controlling data collection, storage, and privacy settings for Azure Personalizer.
ConfigurationL55-L64Configuring Personalizer’s learning behavior: policies, hyperparameters, exploration, apprentice mode, explainability, model export, and learning loop settings.
Integrations & Coding PatternsL65-L68Using the Personalizer local inference SDK for low-latency, offline/edge scenarios, including setup, integration patterns, and best practices for calling the model locally.
分类行范围描述
故障排查L34-L38诊断并解决Azure Personalizer常见问题，包括配置、学习行为、低质量推荐、API错误以及集成或数据/特征问题。
决策制定L39-L43指导何时使用单槽与多槽Personalizer，针对不同个性化需求对比场景、行为和设计权衡。
限制与配额L44-L48指导针对高流量工作负载扩展Personalizer、容量规划、吞吐量/延迟预期以及Azure限制与配额下的性能考量。
安全L49-L54配置静态加密（包括客户管理密钥）并控制Azure Personalizer的数据收集、存储和隐私设置。
配置L55-L64配置Personalizer的学习行为：策略、超参数、探索、学徒模式、可解释性、模型导出和学习循环设置。
集成与编码模式L65-L68使用Personalizer本地推理SDK实现低延迟、离线/边缘场景，包括设置、集成模式和本地调用模型的最佳实践。

Troubleshooting

故障排查

TopicURL
Troubleshoot common Azure Personalizer issueshttps://learn.microsoft.com/en-us/azure/ai-services/personalizer/frequently-asked-questions
主题链接
排查Azure Personalizer常见问题https://learn.microsoft.com/en-us/azure/ai-services/personalizer/frequently-asked-questions

Decision Making

决策制定

TopicURL
Choose between single-slot and multi-slot Personalizerhttps://learn.microsoft.com/en-us/azure/ai-services/personalizer/concept-multi-slot-personalization
主题链接
选择单槽与多槽Personalizerhttps://learn.microsoft.com/en-us/azure/ai-services/personalizer/concept-multi-slot-personalization

Limits & Quotas

限制与配额

TopicURL
Plan scalability and performance for Personalizer workloadshttps://learn.microsoft.com/en-us/azure/ai-services/personalizer/concepts-scalability-performance
主题链接
规划Personalizer工作负载的可扩展性和性能https://learn.microsoft.com/en-us/azure/ai-services/personalizer/concepts-scalability-performance

Security

安全

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
主题链接
为Personalizer配置静态数据加密和CMKhttps://learn.microsoft.com/en-us/azure/ai-services/personalizer/encrypt-data-at-rest
管理Personalizer中的数据使用和隐私https://learn.microsoft.com/en-us/azure/ai-services/personalizer/responsible-data-and-privacy

Configuration

配置

TopicURL
Configure learning policy and hyperparameters in Personalizerhttps://learn.microsoft.com/en-us/azure/ai-services/personalizer/concept-active-learning
Configure exploration settings for Azure Personalizerhttps://learn.microsoft.com/en-us/azure/ai-services/personalizer/concepts-exploration
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
Export and manage Personalizer model and learning settingshttps://learn.microsoft.com/en-us/azure/ai-services/personalizer/how-to-manage-model
Configure Azure Personalizer learning loop settingshttps://learn.microsoft.com/en-us/azure/ai-services/personalizer/how-to-settings
主题链接
在Personalizer中配置学习策略和超参数https://learn.microsoft.com/en-us/azure/ai-services/personalizer/concept-active-learning
为Azure Personalizer配置探索设置https://learn.microsoft.com/en-us/azure/ai-services/personalizer/concepts-exploration
在Personalizer中启用并使用推理可解释性https://learn.microsoft.com/en-us/azure/ai-services/personalizer/how-to-inference-explainability
在Personalizer中配置学徒模式学习行为https://learn.microsoft.com/en-us/azure/ai-services/personalizer/how-to-learning-behavior
导出并管理Personalizer模型和学习设置https://learn.microsoft.com/en-us/azure/ai-services/personalizer/how-to-manage-model
配置Azure Personalizer学习循环设置https://learn.microsoft.com/en-us/azure/ai-services/personalizer/how-to-settings

Integrations & Coding Patterns

集成与编码模式

TopicURL
Use Personalizer local inference SDK for low latencyhttps://learn.microsoft.com/en-us/azure/ai-services/personalizer/how-to-thick-client
主题链接
使用Personalizer本地推理SDK实现低延迟https://learn.microsoft.com/en-us/azure/ai-services/personalizer/how-to-thick-client