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azure-face

Expert knowledge for Azure AI Face development including troubleshooting, best practices, decision making, limits & quotas, security, and integrations & coding patterns. Use when using Face detection, identification, verification, liveness, PersonGroup/Directory, or Face API quotas, and other Azure AI Face related development tasks. Not for Azure AI Vision (use azure-ai-vision), Azure AI Custom Vision (use azure-custom-vision), Azure AI Video Indexer (use azure-video-indexer), Azure AI Document Intelligence (use azure-document-intelligence).

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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.md5.9 KB

SKILL.md（原文）

安装前可以查看交给 AI 代理的指令内容。

Azure AI Face Skill

This skill provides expert guidance for Azure AI Face. Covers troubleshooting, best practices, decision making, limits & quotas, security, 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 fixing Azure Face API failures by interpreting error codes, understanding causes (quota, auth, input issues), and applying recommended resolutions.
Best Practices	L39-L47	Guidance on enrolling faces, scaling PersonGroup/PersonDirectory, optimizing performance/latency, and building consent-aware, high-capacity Azure Face enrollment workflows.
Decision Making	L48-L53	Guidance on choosing, configuring, and tuning Azure Face detection and recognition models, including model types, capabilities, parameters, and selection trade-offs.
Limits & Quotas	L54-L59	Scaling PersonGroup for large face datasets and understanding Face API quotas, rate limits, and maximum sizes for persons, faces, and training operations.
Security	L60-L69	Security and compliance for Face and liveness: abuse monitoring, token-based access control, network isolation, encryption/CMK, shared responsibility, and secure SDK version management.
Integrations & Coding Patterns	L70-L73	How to call Azure Face API endpoints, use key operations (detect, identify, verify, find similar), and structure requests/responses in your applications.

Troubleshooting

Topic	URL
Resolve Azure Face API errors using error codes	https://learn.microsoft.com/en-us/azure/ai-services/face/reference-face-error-codes

Best Practices

Topic	URL
Apply best practices for Azure Face enrollment	https://learn.microsoft.com/en-us/azure/ai-services/face/enrollment-overview
Add many faces to PersonGroup efficiently	https://learn.microsoft.com/en-us/azure/ai-services/face/how-to/add-faces
Optimize Azure Face performance and reduce latency	https://learn.microsoft.com/en-us/azure/ai-services/face/how-to/mitigate-latency
Use PersonDirectory for high-capacity face storage	https://learn.microsoft.com/en-us/azure/ai-services/face/how-to/use-persondirectory
Implement consent-focused Face enrollment app	https://learn.microsoft.com/en-us/azure/ai-services/face/tutorials/build-enrollment-app

Decision Making

Topic	URL
Choose and specify Azure Face detection models	https://learn.microsoft.com/en-us/azure/ai-services/face/how-to/specify-detection-model
Select and configure Azure Face recognition models	https://learn.microsoft.com/en-us/azure/ai-services/face/how-to/specify-recognition-model

Limits & Quotas

Topic	URL
Scale PersonGroup objects to large Face datasets	https://learn.microsoft.com/en-us/azure/ai-services/face/how-to/use-large-scale
Review Azure Face service quotas and limits	https://learn.microsoft.com/en-us/azure/ai-services/face/identity-quotas-limits

Security

Topic	URL
Configure abuse monitoring for Face liveness detection	https://learn.microsoft.com/en-us/azure/ai-services/face/concept-liveness-abuse-monitoring
Manage Face API access with limited tokens	https://learn.microsoft.com/en-us/azure/ai-services/face/how-to/identity-access-token
Use Face liveness detection with network isolation	https://learn.microsoft.com/en-us/azure/ai-services/face/how-to/liveness-use-network-isolation
Configure encryption and CMK for Azure Face data	https://learn.microsoft.com/en-us/azure/ai-services/face/identity-encrypt-data-at-rest
Secure Face liveness solutions with shared responsibility	https://learn.microsoft.com/en-us/azure/ai-services/face/liveness-detection-shared-responsibility
Manage liveness client SDK versions for security	https://learn.microsoft.com/en-us/azure/ai-services/face/sdk/understand-the-liveness-sdk-versions

Integrations & Coding Patterns

Topic	URL
Use Azure Face API endpoints and operations	https://learn.microsoft.com/en-us/azure/ai-services/face/identity-api-reference

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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。