About azure-face
azure-face is a guidance skill for developers and agents working with Azure AI Face. It combines local references with remote documentation on API use, security, scaling, and troubleshooting.
Key features
- 01Troubleshooting API errors
- 02Face enrollment guidance
- 03Detection and recognition model selection
- 04Quota and scaling guidance
- 05Security and access controls
- 06API integration patterns
Use cases
- 01Diagnosing Face API failures
- 02Planning large-scale face enrollment
- 03Selecting detection and recognition models
- 04Reviewing liveness security controls
MCP support
The skill can fetch remote documentation through mcp_microsoftdocs:microsoft_docs_fetch; it also documents a fetch_webpage fallback.
Install
Copy the command and run it in a terminal.
npx skills add https:/ / github.com/ microsoftdocs/ agent-skills --skill azure-faceAfter installing, type/azure-facein Claude Code to confirm it loaded.
Details
From the project READMEAzure 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), useread_filewith the specified lines. For categories with file links (e.g.,[security.md](security.md)), useread_fileon the linked reference file
IMPORTANT for Agent: If
metadata.generated_atis more than 3 months old, suggest the user pull the latest version from the repository. Ifmcp_microsoftdocstools 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_fetchwith query stringfrom=learn-agent-skill. Returns Markdown. - Fallback: Use
fetch_webpagewith query stringfrom=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 |