microsoft-foundry-tools

name	microsoft-foundry-tools
description	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 Content Moderator, Content Understanding analyzers, document extraction, routing, or secure Foundry setup, and other Microsoft Foundry Tools related development tasks. Not for Microsoft Foundry (use microsoft-foundry), Microsoft Foundry Classic (use microsoft-foundry-classic), Microsoft Foundry Local (use microsoft-foundry-local).
compatibility	Requires network access. Uses mcp_microsoftdocs:microsoft_docs_fetch or fetch_webpage to retrieve documentation.
metadata	{"generated_at":"2026-04-19","generator":"docs2skills/1.0.0"}

Microsoft Foundry Tools Skill

This 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.

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
Best Practices	L35-L41	Guidance on improving Content Understanding accuracy, grounding and confidence in document extraction, and migrating from preview to GA Content Understanding APIs.
Decision Making	L42-L48	Guides for choosing the right Azure AI/Foundry tool for document processing and estimating Content Understanding costs and pricing plans.
Architecture & Design Patterns	L49-L53	Designing and configuring how Content Understanding analyzers are mapped to specific model deployments, including routing strategies and deployment architecture patterns.
Limits & Quotas	L54-L61	Quotas, limits, and language support for Azure Content Moderator and Content Understanding, including image/list caps, API usage constraints, and .NET sample considerations.
Security	L62-L66	Securing Foundry: auth methods, Entra-only access, keys/Key Vault, CMK encryption, DLP, VNet rules, API key rotation, Azure Policy and regulatory compliance configuration
Configuration	L67-L77	Configuring Foundry environments and resources: credentials, subdomains, ARM provisioning, logging, and detailed setup for Content Understanding analyzers, layouts, images, faces, and routing.
Integrations & Coding Patterns	L78-L92	Using Content Moderator and Content Understanding via REST/.NET: text/image/video moderation, term lists, multimodal analysis, and consuming Markdown/structured outputs

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 extraction with confidence and grounding	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/document/analyzer-improvement
Migrate Azure Content Understanding preview APIs to GA	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/migration-preview-to-ga

Decision Making

Topic	URL
Choose Azure AI tool for document processing	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/choosing-right-ai-tool
Choose between Foundry and Content Understanding Studio features	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/foundry-vs-content-understanding-studio
Estimate and plan Content Understanding pricing	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/pricing-explainer

Architecture & Design Patterns

Topic	URL
Map Content Understanding analyzers to model deployments	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/models-deployments

Limits & Quotas

Topic	URL
Use Content Moderator image lists within quota limits	https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/image-lists-quickstart-dotnet
Use supported languages in Content Moderator API	https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/language-support
Apply Content Moderator .NET samples with list limits	https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/samples-dotnet
Review Azure 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 with keys and identities	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
Use and customize Content Understanding prebuilt analyzers	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/prebuilt-analyzers
Configure document layout analysis with Content Understanding	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/document/elements
Configure face detection and recognition in Content Understanding	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/face/overview
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
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
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

Integrations & Coding Patterns

Topic	URL
Content Moderator REST API operations reference	https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/api-reference
Integrate Content Moderator via .NET client library	https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/client-libraries
Call Content Moderator image moderation APIs	https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/image-moderation-api
Call Content Moderator REST APIs from C# samples	https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/samples-rest
Use .NET SDK term lists with Content Moderator	https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/term-lists-quickstart-dotnet
Use Content Moderator text moderation APIs	https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/text-moderation-api
Moderate video content using Content Moderator .NET SDK	https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/video-moderation-api
Consume Content Understanding document Markdown output	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/document/markdown
Call Content Understanding REST API for multimodal data	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/quickstart/use-rest-api
Create custom Content Understanding analyzers via REST API	https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/tutorial/create-custom-analyzer