Skip to content
Docksoft

Microsoft Foundry Tools

B

microsoft-foundry-tools

Tooling and CLI patterns for Microsoft Foundry: deployment helpers, scripts, and integration utilities. Requires the mcp_microsoftdocs MCP for live docs.

microsoftfoundrytoolsclideployment

Install

npx skills add MicrosoftDocs/Agent-Skills
Author
Microsoft
License
CC-BY-4.0
Updated
May 2026
Type
Single skill
Document
8.6 KB
Platforms
Claude Code, Codex, Cursor, Gemini Cli, Github Copilot, Multi Platform
View source

SKILL.md

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

CategoryLinesDescription
Best PracticesL35-L40Guidance on improving Content Understanding accuracy, grounding and confidence in document extraction, and migrating from preview to GA Content Understanding APIs.
Decision MakingL41-L48Guidance on choosing Foundry vs Content Understanding tools, selecting Azure AI document processing options, migrating preview to GA APIs, and estimating Content Understanding costs.
Architecture & Design PatternsL49-L53Guidance on choosing and configuring deployment options (serverless, managed, custom) for Content Understanding models, including trade-offs, scalability, and integration patterns.
Limits & QuotasL54-L61Quotas, limits, and supported languages for Content Moderator image/list APIs and Content Understanding, plus .NET samples showing how to stay within list and usage limits.
SecurityL62-L66Securing Foundry: auth methods, Entra-only access, keys/Key Vault, CMK encryption, DLP, VNet rules, API key rotation, Azure Policy and regulatory compliance configuration
ConfigurationL67-L76Configuring and customizing Content Understanding analyzers (prebuilt and custom), document layout, face detection, and cross-resource capacity settings.
Integrations & Coding PatternsL77-L91Using Content Moderator and Content Understanding via REST/.NET: text/image/video moderation, term lists, multimodal analysis, and consuming Markdown/structured outputs

Best Practices

TopicURL
Apply best practices for Content Understanding accuracyhttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/best-practices
Improve document extraction with confidence and groundinghttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/document/analyzer-improvement

Decision Making

TopicURL
Choose Azure AI tool for document processinghttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/choosing-right-ai-tool
Choose between Foundry and Content Understanding Studio featureshttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/foundry-vs-content-understanding-studio
Migrate Content Understanding from preview to GA APIshttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/migration-preview-to-ga
Estimate and plan Content Understanding pricinghttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/pricing-explainer

Architecture & Design Patterns

TopicURL
Select model deployment options for Content Understandinghttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/models-deployments

Limits & Quotas

TopicURL
Use Content Moderator image lists within quota limitshttps://learn.microsoft.com/en-us/azure/ai-services/content-moderator/image-lists-quickstart-dotnet
Use supported languages in Content Moderator APIhttps://learn.microsoft.com/en-us/azure/ai-services/content-moderator/language-support
Apply Content Moderator .NET samples with list limitshttps://learn.microsoft.com/en-us/azure/ai-services/content-moderator/samples-dotnet
Content Understanding service quotas and limits referencehttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/service-limits

Security

TopicURL
Secure Content Understanding with keys and identitieshttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/secure-communications

Configuration

TopicURL
Configure and reference analyzers in Azure Content Understandinghttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/analyzer-reference
Use and customize Content Understanding prebuilt analyzershttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/prebuilt-analyzers
Configure document layout analysis with Content Understandinghttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/document/elements
Configure face detection and recognition in Content Understandinghttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/face/overview
Configure cross-resource capacity for Content Understandinghttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/bring-your-own-cross-resource-capacity
Build and refine custom analyzers in Content Understanding Studiohttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/customize-analyzer-content-understanding-studio

Integrations & Coding Patterns

TopicURL
Content Moderator REST API operations referencehttps://learn.microsoft.com/en-us/azure/ai-services/content-moderator/api-reference
Integrate Content Moderator via .NET client libraryhttps://learn.microsoft.com/en-us/azure/ai-services/content-moderator/client-libraries
Call Content Moderator image moderation APIshttps://learn.microsoft.com/en-us/azure/ai-services/content-moderator/image-moderation-api
Call Content Moderator REST APIs from C# sampleshttps://learn.microsoft.com/en-us/azure/ai-services/content-moderator/samples-rest
Use .NET SDK term lists with Content Moderatorhttps://learn.microsoft.com/en-us/azure/ai-services/content-moderator/term-lists-quickstart-dotnet
Use Content Moderator text moderation APIshttps://learn.microsoft.com/en-us/azure/ai-services/content-moderator/text-moderation-api
Moderate video content using Content Moderator .NET SDKhttps://learn.microsoft.com/en-us/azure/ai-services/content-moderator/video-moderation-api
Consume Content Understanding document Markdown outputhttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/document/markdown
Call Content Understanding REST API for multimodal datahttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/quickstart/use-rest-api
Create custom Content Understanding analyzers via REST APIhttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/tutorial/create-custom-analyzer
Extract structured audiovisual content with Content Understandinghttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/video/elements
Use audiovisual Markdown output from Content Understandinghttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/video/markdown

Related

AI/ML Development

S

.NET AI

dotnet-ai

AI and ML skills for .NET 8+: technology selection (ML.NET, Microsoft.Extensions.AI, Microsoft Agent Framework, Copilot SDK, ONNX, OllamaSharp), LLM integration, agentic workflows, RAG pipelines, MCP server creation.

claude-codegithub-copilotcursor+1MIT

AI/ML Development

B

AI Research Skills

ai-research-skills

77 AI research skills across 20 categories covering training, inference, and MLOps workflows.

claude-codeMIT

AI/ML Development

A

Azure Cognitive Search

azure-cognitive-search

Build search and RAG indexes on Azure Cognitive Search: vector + hybrid search, semantic ranking, indexers, and skillsets. Requires the mcp_microsoftdocs MCP for live docs.

claude-codecodexcursor+3CC-BY-4.0

Agent tooling

Want agents that know your stack?

This index is ours, and so is the tooling behind it. If your team wants agents that understand how your own systems actually work, that is a thing we build.

Contact the dock

One address, read by the people who would do the work. No intake form, no calendar link — just an email.

tphamdn@gmail.com
Other reasons to writeWe reply within two business days