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azure-content-understanding

Expert knowledge for Azure Content Understanding in Foundry Tools development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. Use when building Content Understanding analyzers, RAG document flows, agentic workflows, REST/SDK calls, or GA migrations, and other Azure Content Understanding in Foundry Tools related development tasks. Not for Content Safety in Foundry Control Plane (use azure-content-safety), Azure Speech in Foundry Tools (use azure-speech), Azure AI Vision (use azure-ai-vision), Azure AI Document Intelligence (use azure-document-intelligence).

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Azure Content Understanding in Foundry Tools Skill

This skill provides expert guidance for Azure Content Understanding in Foundry Tools. Covers troubleshooting, 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

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	L36-L40	Using diagnostics from the Content Understanding REST API to investigate failures, interpret error codes, and troubleshoot processing or configuration issues.
Best Practices	L41-L46	Improving Content Understanding accuracy using layout, labels, and feedback, plus using confidence scores and grounding to validate and refine document analysis results.
Decision Making	L47-L55	Guidance on choosing Azure AI/Foundry tools, model deployments, and Studio vs Foundry; migrating Content Understanding from preview to GA; and estimating/optimizing pricing.
Architecture & Design Patterns	L56-L62	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	L63-L68	Guidance on safe use of synchronous Content Understanding calls plus detailed quotas, rate limits, and throughput constraints for Foundry Tools.
Security	L69-L74	Configuring security for Content Understanding: setting guardrails on analyzer outputs, securing analyzers and data, access control, and safe handling of sensitive content.
Configuration	L75-L88	Configuring and customizing Content Understanding analyzers, classifiers, workflows, and audiovisual/Markdown outputs, including creating, copying, and managing custom analyzers and Foundry resources.
Integrations & Coding Patterns	L89-L94	Patterns and code samples for calling Content Understanding via REST/SDKs, integrating with Microsoft Agent Framework/LangChain, and implementing agentic workflows.

Troubleshooting

Topic	URL
Use diagnostics from Content Understanding REST API	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/retrieve-diagnostics

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 model deployments for Content Understanding analyzers	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/models-deployments
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
Review Content Understanding quotas and limits in Foundry Tools	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/service-limits

Security

Topic	URL
Configure guardrails for Content Understanding results	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/guardrails
Secure Content Understanding analyzers and data	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/secure-communications

Configuration

Topic	URL
Configure and customize Content Understanding analyzers	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.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/classification-content-understanding-studio
Copy custom analyzers within and across resources	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/copy-analyzers
Create and manage Microsoft Foundry resources	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/create-multi-service-resource
Build and refine custom analyzers in Studio	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/customize-analyzer-content-understanding-studio
Create custom analyzers via Content Understanding REST API	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/tutorial/create-custom-analyzer
Configure audiovisual analysis and structured output	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/video/elements
Use Markdown output for audiovisual content	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/video/markdown

Integrations & Coding Patterns

Topic	URL
Integrate Content Understanding with Microsoft Agent Framework	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/integrations/agent-framework
Use Content Understanding as a LangChain document loader	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/integrations/langchain
Call Content Understanding REST APIs and SDKs	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/quickstart/use-rest-api

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