git:20260831.9fc50b0 to git:20260907.90ec55f

16 added, 10 removed. Audit A to A.

---

name: azure-content-understanding

- description: 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).

+ description: 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 designing Content Understanding analyzers, RAG document flows, audiovisual analysis, REST/SDK calls, or agentic workflows, and other Azure Content Understanding in Foundry Tools related development tasks. Not for Content Safety in Foundry Control Plane (use azure-content-safety), Azure AI Language (use azure-language-service), Azure AI Document Intelligence (use azure-document-intelligence), Azure Speech in Foundry Tools (use azure-speech).

compatibility: Requires network access. Uses mcp_microsoftdocs:microsoft_docs_fetch or fetch_webpage to retrieve documentation.

metadata:

- generated_at: "2026-08-31"

+ generated_at: "2026-09-06"

generator: "docs2skills/1.0.0"

---

# 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.

+ 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](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. |

+ | 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-L56 | 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 | L57-L63 | 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 | L64-L69 | 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 | L70-L74 | Securing Content Understanding analyzers and data: encryption, access control, network isolation, compliance, and best practices for protecting customer content and telemetry. |

+ | Configuration | L75-L88 | 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 | L89-L95 | 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 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.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 |

| Implement agentic mode with Content Understanding API | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/quickstart/agentic-mode |

| Call Content Understanding REST APIs and SDKs | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/quickstart/use-rest-api |