azure-content-understanding
Expert knowledge for Azure Content Understanding in Foundry Tools development including best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. Use when building analyzers/classifiers, RAG document flows, audiovisual analysis, Markdown outputs, or agentic workflows, and other Azure Content Understanding in Foundry Tools related development tasks. Not for Azure Speech in Foundry Tools (use azure-speech), Content Safety in Foundry Control Plane (use azure-content-safety), Azure AI Vision (use azure-ai-vision), Azure AI Document Intelligence (use azure-document-intelligence).
git clone --depth 1 https://github.com/MicrosoftDocs/Agent-Skills /tmp/azure-content-understanding && cp -r /tmp/azure-content-understanding/skills/azure-content-understanding ~/.claude/skills/azure-content-understandingSKILL.md
# Azure Content Understanding in Foundry Tools Skill This skill provides expert guidance for Azure Content Understanding in Foundry Tools. Covers best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, 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](https://github.com/MicrosoftDocs/mcp/blob/main/README.md) 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 | |----------|-------|-------------| | Best Practices | L35-L40 | Improving Content Understanding accuracy using layout, labels, and feedback, plus using confidence scores and grounding to validate and refine document analysis results. | | Decision Making | L41-L50 | Guidance on choosing tools, deployments, and analyzers, deciding between Studio vs Foundry, migrating preview to GA, and estimating/optimizing Content Understanding costs | | Architecture & Design Patterns | L51-L57 | Guidance on when to use agentic mode, how to design RAG-based document solutions, and how to build RPA workflows using Azure Content Understanding. | | Limits & Quotas | L58-L63 | Guidance on safe use of synchronous Content Understanding calls and detailed quotas/limits (throughput, payload sizes, concurrency) to avoid throttling and design compliant workloads | | Security | L64-L68 | Securing Content Understanding analyzers and data: encryption, access control, network isolation, compliance, and best practices for protecting customer content and telemetry. | | Configuration | L69-L82 | Configuring and managing Content Understanding: analyzers, classifiers, splitting, workflows, capacity, audiovisual analysis, Markdown outputs, and creating/customizing analyzers via Studio or REST. | | Integrations & Coding Patterns | L83-L89 | Patterns and code samples for calling Content Understanding via REST/SDKs, integrating with Microsoft Agent Framework/LangChain, and implementing agentic workflows. | ### Best Practices | Topic | URL | |-------|-----| | Apply best practices for Content Understanding accuracy | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/best-practices | | Improve document analysis with confidence and grounding | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/document/analyzer-improvement | ### Decision Making | Topic | URL | |-------|-----| | Choose Azure AI tools for document processing | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/choosing-right-ai-tool | | Choose and map Foundry model deployments for analyzers | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/models-deployments | | Select and customize Content Understanding prebuilt analyzers | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/prebuilt-analyzers | | Choose between Content Understanding Studio and Foundry | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/foundry-vs-content-understanding-studio | | Migrate Content Understanding from preview to GA | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/migration-preview-to-ga | | Estimate and optimize Content Understanding pricing | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/pricing-explainer | ### Architecture & Design Patterns | Topic | URL | |-------|-----| | Decide when to use agentic mode for documents | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/agentic-mode | | Design a RAG solution with Content Understanding | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/tutorial/build-rag-solution | | Design RPA workflows using Content Understanding | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/tutorial/robotic-process-automation | ### Limits & Quotas | Topic | URL | |-------|-----| | Use synchronous Content Understanding operations safely | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/quickstart/use-synchronous-rest-api | | Apply Content Understanding service quotas and limits | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/service-limits | ### Security | Topic | URL | |-------|-----| | Secure Content Understanding analyzers and data | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/secure-communications | ### Configuration | Topic | URL | |-------|-----| | Configure Content Understanding analyzers and parameters | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/analyzer-reference | | Configure Content Understanding classifier and splitting | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/classifier | | Interpret Content Understanding Markdown document output | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/document/markdown | | Configure classification and routing workflows in Content Understanding | https://learn.
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).
Expert knowledge for Azure Advisor development including best practices, decision making, limits & quotas, security, configuration, and integrations & coding patterns. Use when tuning Advisor alerts, digests, and states, bulk-fixing savings, or querying recommendations via Resource Graph, and other Azure Advisor related development tasks. Not for Cost Management (use azure-cost-management), Azure Monitor (use azure-monitor), Azure Policy (use azure-policy), Azure Security (use azure-security).
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).
Expert knowledge for Azure Kubernetes Service Edge Essentials development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when deploying AKS Edge/Hybrid with Arc, Azure Local, Windows Server nodes, IoT/OPC/ONVIF, or TPM workloads, and other Azure Kubernetes Service Edge Essentials related development tasks. Not for Azure Kubernetes Service (AKS) (use azure-kubernetes-service), Azure Container Apps (use azure-container-apps), Azure Red Hat OpenShift (use azure-redhat-openshift), Azure Stack Edge (use azure-stack-edge).
Expert knowledge for Azure Analysis Services development including troubleshooting. Use when resolving server connectivity, firewall/VNet, DNS, client connection, or network error issues, and other Azure Analysis Services related development tasks. Not for Azure Synapse Analytics (use azure-synapse-analytics), Azure SQL Database (use azure-sql-database), Azure SQL Managed Instance (use azure-sql-managed-instance), SQL Server on Azure Virtual Machines (use azure-sql-virtual-machines).
Expert knowledge for Azure AI Anomaly Detector development including troubleshooting, best practices, limits & quotas, configuration, and deployment. Use when tuning Docker-based Anomaly Detector, ACI or IoT Edge deployments, univariate/multivariate APIs, or service limits, and other Azure AI Anomaly Detector related development tasks. Not for Azure AI Metrics Advisor (use azure-metrics-advisor), Azure Monitor (use azure-monitor), Azure Machine Learning (use azure-machine-learning).
Expert knowledge for Azure Api Center development including best practices, security, configuration, integrations & coding patterns, and deployment. Use when configuring API Center instances, portal auth, GitHub-based lint/registration, portal self-hosting, or API sync, and other Azure Api Center related development tasks. Not for Azure API Management (use azure-api-management), Azure Resource Manager (use azure-resource-manager), Azure Portal (use azure-portal), Azure Monitor (use azure-monitor).
Expert knowledge for Azure API Management development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when integrating APIM with AI backends, Entra/OAuth, VNet/gateways, self-hosted gateways, or multi-region scaling, and other Azure API Management related development tasks. Not for Azure App Service (use azure-app-service), Azure Functions (use azure-functions), Azure Logic Apps (use azure-logic-apps), Azure Service Bus (use azure-service-bus).