{"id":"c1039b95-2011-493f-abb1-063476b533f1","shortId":"JrdZBx","kind":"skill","title":"microsoft-foundry-tools","tagline":"Expert knowledge for Microsoft Foundry Tools (aka Azure AI services, Azure Cognitive Services) development including best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. Use when using Conte","description":"# Microsoft Foundry Tools Skill\n\nThis skill provides expert guidance for Microsoft 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.\n\n## How to Use This Skill\n\n> **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\n\n> **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)\n\nThis skill requires **network access** to fetch documentation content:\n- **Preferred**: Use `mcp_microsoftdocs:microsoft_docs_fetch` with query string `from=learn-agent-skill`. Returns Markdown.\n- **Fallback**: Use `fetch_webpage` with query string `from=learn-agent-skill&accept=text/markdown`. Returns Markdown.\n\n## Category Index\n\n| Category | Lines | Description |\n|----------|-------|-------------|\n| Best Practices | L35-L40 | Improving Content Understanding accuracy, document extraction quality, and using confidence scores/grounding to make extractions more reliable and trustworthy |\n| Decision Making | L41-L49 | Guides for choosing and comparing Foundry/Content Understanding tools and modes, planning pricing, and migrating from preview to GA document processing APIs |\n| Architecture & Design Patterns | L50-L54 | Designing and configuring how Content Understanding analyzers are mapped to specific model deployments, including routing strategies and deployment architecture patterns. |\n| Limits & Quotas | L55-L62 | Quotas, limits, and supported languages for Content Moderator and Content Understanding, including image/list caps, usage constraints, and .NET sample considerations. |\n| Security | L63-L67 | Securing Foundry: auth methods, Entra-only access, keys/Key Vault, CMK encryption, DLP, VNet rules, API key rotation, Azure Policy and regulatory compliance configuration |\n| Configuration | L68-L78 | Configuring Foundry environments and resources: credentials, subdomains, ARM provisioning, logging, and detailed setup for Content Understanding analyzers, layouts, images, faces, and routing. |\n| Integrations & Coding Patterns | L79-L93 | Using Content Moderator and Content Understanding via REST/.NET: text/image/video moderation, term lists, multimodal analysis, and consuming Markdown/structured outputs |\n\n### Best Practices\n| Topic | URL |\n|-------|-----|\n| Apply best practices for Content Understanding accuracy | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/best-practices |\n| Improve document extraction with confidence and grounding | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/document/analyzer-improvement |\n\n### Decision Making\n| Topic | URL |\n|-------|-----|\n| Choose Azure AI tool for document processing | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/choosing-right-ai-tool |\n| Choose between Content Understanding standard and pro modes | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/standard-pro-modes |\n| Compare Foundry vs Content Understanding Studio features | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/foundry-vs-content-understanding-studio |\n| Migrate Content Understanding from preview to GA APIs | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/migration-preview-to-ga |\n| Estimate and plan Content Understanding pricing | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/pricing-explainer |\n\n### Architecture & Design Patterns\n| Topic | URL |\n|-------|-----|\n| Map Content Understanding analyzers to model deployments | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/models-deployments |\n\n### Limits & Quotas\n| Topic | URL |\n|-------|-----|\n| Use Content Moderator image lists within quota limits | https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/image-lists-quickstart-dotnet |\n| Use supported languages in Content Moderator API | https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/language-support |\n| Apply Content Moderator .NET samples with list limits | https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/samples-dotnet |\n| Review Content Understanding service quotas and limits | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/service-limits |\n\n### Security\n| Topic | URL |\n|-------|-----|\n| Secure Content Understanding with keys and identities | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/secure-communications |\n\n### Configuration\n| Topic | URL |\n|-------|-----|\n| Configure Content Understanding analyzers and parameters | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/analyzer-reference |\n| Use and customize Content Understanding prebuilt analyzers | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/prebuilt-analyzers |\n| Configure document layout analysis with Content Understanding | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/document/elements |\n| Configure face detection and recognition in Content Understanding | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/face/overview |\n| Configure classification and routing in Content Understanding Studio | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/classification-content-understanding-studio |\n| Configure Standard and Pro tasks in Foundry classic | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/content-understanding-foundry-classic |\n| Build and refine custom analyzers in Content Understanding Studio | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/customize-analyzer-content-understanding-studio |\n\n### Integrations & Coding Patterns\n| Topic | URL |\n|-------|-----|\n| Content Moderator REST API operations reference | https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/api-reference |\n| Integrate Content Moderator via .NET client library | https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/client-libraries |\n| Call Content Moderator image moderation APIs | https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/image-moderation-api |\n| Call Content Moderator REST APIs from C# samples | https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/samples-rest |\n| Use .NET SDK term lists with Content Moderator | https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/term-lists-quickstart-dotnet |\n| Use Content Moderator text moderation APIs | https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/text-moderation-api |\n| Moderate video content using Content Moderator .NET SDK | https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/video-moderation-api |\n| Consume Content Understanding document Markdown output | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/document/markdown |\n| Call Content Understanding REST API for multimodal data | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/quickstart/use-rest-api |\n| Create custom Content Understanding analyzers via REST API | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/tutorial/create-custom-analyzer |\n| Extract structured audiovisual content with Content Understanding | 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