skills/azure-ai-vision/SKILL.md
Expert knowledge for Azure AI Vision development including decision making, limits & quotas, configuration, integrations & coding patterns, and deployment. Use when using Image Analysis, Read OCR containers, smart-crop thumbnails, background removal, or video frame analysis, and other Azure AI Vision related development tasks. Not for Azure AI Custom Vision (use azure-custom-vision), Azure AI Video Indexer (use azure-video-indexer), Azure AI Document Intelligence (use azure-document-intelligence), Azure AI Immersive Reader (use azure-immersive-reader).
npx skillsauth add microsoftdocs/agent-skills azure-ai-visionInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill provides expert guidance for Azure AI Vision. Covers decision making, limits & quotas, configuration, integrations & coding patterns, and deployment. It combines local quick-reference content with remote documentation fetching capabilities.
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:
mcp_microsoftdocs:microsoft_docs_fetch with query string from=learn-agent-skill. Returns Markdown.fetch_webpage with query string from=learn-agent-skill&accept=text/markdown. Returns Markdown.| Category | Lines | Description | |----------|-------|-------------| | Decision Making | L33-L39 | Guides for planning and executing migrations and upgrades between Azure Vision Image Analysis and Read OCR versions/containers, including breaking changes and app update steps. | | Limits & Quotas | L40-L50 | Limits, thresholds, and taxonomies for Image Analysis: category lists, adult content scores, object/people detection constraints, smart-crop behavior, and OCR language support. | | Configuration | L51-L56 | Configuring Vision Read OCR containers and setting up Azure Blob Storage access for image input, including environment settings, storage permissions, and connection details. | | Integrations & Coding Patterns | L57-L67 | How to call and configure Azure Vision/Read APIs and SDKs for OCR, embeddings, thumbnails, background removal, domain models, and live video frame analysis. | | Deployment | L68-L71 | Installing, configuring, and running the Azure AI Vision Read OCR container locally or on-premises, including prerequisites, deployment steps, and runtime settings. |
| Topic | URL | |-------|-----| | Plan migration from Azure Vision Image Analysis | https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/migration-options | | Migrate to Azure Vision Read OCR container v3.x | https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/read-container-migration-guide | | Upgrade applications from Read v2.x to v3.0 | https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/upgrade-api-versions |
| Topic | URL | |-------|-----| | Reference taxonomy categories for Azure Vision | https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/category-taxonomy | | Understand Image Analysis 3.2 categorization taxonomy limits | https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/concept-categorizing-images | | Interpret adult content detection scores and thresholds | https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/concept-detecting-adult-content | | Use object detection and understand feature limits | https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/concept-object-detection | | Understand Image Analysis 4.0 object detection limits | https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/concept-object-detection-40 | | Use people detection and understand its limits | https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/concept-people-detection | | Check supported languages for Azure Vision OCR | https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/language-support |
| Topic | URL | |-------|-----| | Configure Azure Vision Read OCR containers | https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/computer-vision-resource-container-config | | Configure Azure Blob Storage for Vision image retrieval | https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/how-to/blob-storage-search |
| Topic | URL | |-------|-----| | Call domain-specific models with Azure Vision | https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/concept-detecting-domain-content | | Analyze live video frames with Azure Vision API | https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/how-to/analyze-video | | Call and configure Image Analysis 3.2 API | https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/how-to/call-analyze-image | | Call and configure Image Analysis 4.0 API | https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/how-to/call-analyze-image-40 | | Call and configure Azure Vision Read v3.2 API | https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/how-to/call-read-api | | Use multimodal embeddings for image retrieval | https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/how-to/image-retrieval | | Use OCR client libraries for text extraction | https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/quickstarts-sdk/client-library |
| Topic | URL | |-------|-----| | Install and run Azure Vision Read OCR container | https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/computer-vision-how-to-install-containers |
tools
Expert knowledge for Microsoft Foundry (aka Azure AI Foundry) development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building Foundry agents with Azure OpenAI, model router patterns, MCP tools, private networking, or eval workflows, and other Microsoft Foundry related development tasks. Not for Microsoft Foundry Classic (use microsoft-foundry-classic), Microsoft Foundry Local (use microsoft-foundry-local), Microsoft Foundry Tools (use microsoft-foundry-tools).
tools
Expert knowledge for Microsoft Foundry Local (aka Azure AI Foundry Local) development including troubleshooting, decision making, configuration, and integrations & coding patterns. Use when calling Foundry Local REST/chat APIs, tools, transcription, LangChain apps, Olive HF compilation, or CLI, and other Microsoft Foundry Local related development tasks. Not for Microsoft Foundry (use microsoft-foundry), Microsoft Foundry Classic (use microsoft-foundry-classic), Microsoft Foundry Tools (use microsoft-foundry-tools), Azure Local (use azure-local).
tools
Expert knowledge for Microsoft Foundry Classic (aka Azure AI Foundry classic) development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building Foundry agents, configuring model routing, securing VNets/Private Link, integrating tools/SDKs, or deploying hubs, and other Microsoft Foundry Classic related development tasks. Not for Microsoft Foundry (use microsoft-foundry), Microsoft Foundry Local (use microsoft-foundry-local), Microsoft Foundry Tools (use microsoft-foundry-tools).
development
Expert guidance for designing, assessing, and optimizing Azure workloads using Azure Well Architected. Covers design review checklists, recommendations, design principles, tradeoffs, service guides, workload patterns, and assessment questions. Use when designing AI, HPC, SaaS, AVD, or mission-critical workloads with WAF-aligned Azure patterns and guidance, and other Azure Well Architected related development tasks.