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).
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.