> microsoft-foundry-tools
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, integrations & coding patterns, and deployment. Use when using Content Understanding analyzers, Content Moderator APIs, Foundry containers, VNet/Key Vault security, or Entra auth, and other Microsoft Foundry Tools related development tasks. Not for Microsoft Foundry (use micr
curl "https://skillshub.wtf/MicrosoftDocs/Agent-Skills/microsoft-foundry-tools?format=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, integrations & coding patterns, and deployment. 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), useread_filewith the specified lines. For categories with file links (e.g.,[security.md](security.md)), useread_fileon the linked reference file
IMPORTANT for Agent: If
metadata.generated_atis more than 3 months old, suggest the user pull the latest version from the repository. Ifmcp_microsoftdocstools 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_fetchwith query stringfrom=learn-agent-skill. Returns Markdown. - Fallback: Use
fetch_webpagewith query stringfrom=learn-agent-skill&accept=text/markdown. Returns Markdown.
Category Index
| Category | Lines | Description |
|---|---|---|
| Best Practices | L36-L41 | Improving Content Understanding accuracy, document extraction quality, and using confidence scores/grounding to make extractions more reliable and trustworthy |
| Decision Making | L42-L51 | Guidance on choosing Foundry pricing tiers, selecting Azure AI/Content Understanding modes and tools, comparing Foundry vs Studio, migration steps, and estimating Content Understanding costs. |
| Architecture & Design Patterns | L52-L56 | Designing and configuring how Content Understanding analyzers are mapped to specific model deployments, including routing strategies and deployment architecture patterns. |
| Limits & Quotas | L57-L65 | Quotas, rate limits, and throughput for Foundry Tools and Content Moderator/Understanding APIs, including autoscale settings, image/list limits, and supported language constraints. |
| Security | L66-L79 | 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 | L80-L98 | 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 | L99-L114 | Using Content Moderator and Content Understanding via REST/.NET: calling text/image/video APIs, managing term lists, and consuming/creating multimodal Markdown and custom analyzers. |
| Deployment | L115-L121 | Deploying Foundry Tools as containers: setup on Azure AI and Azure Container Instances, offline/disconnected deployment, and multi-container orchestration with Docker Compose. |
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 |
Decision Making
| Topic | URL |
|---|---|
| Choose and use Foundry commitment tier pricing | https://learn.microsoft.com/en-us/azure/ai-services/commitment-tier |
| Choose Azure AI tools for document processing | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/choosing-right-ai-tool |
| Choose between Content Understanding standard and pro modes | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/standard-pro-modes |
| Compare Foundry vs Content Understanding Studio features | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/foundry-vs-content-understanding-studio |
| 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 |
| 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 |
|---|---|
| Configure autoscale rate limits for Foundry Tools | https://learn.microsoft.com/en-us/azure/ai-services/autoscale |
| 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 |
| Content Understanding quotas, limits, and throughput | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/service-limits |
Security
Configuration
Integrations & Coding Patterns
Deployment
| Topic | URL |
|---|---|
| Deploy Foundry Tools using Azure AI containers | https://learn.microsoft.com/en-us/azure/ai-services/cognitive-services-container-support |
| Deploy Foundry containers to Azure Container Instances | https://learn.microsoft.com/en-us/azure/ai-services/containers/azure-container-instance-recipe |
| Run Foundry containers in disconnected environments | https://learn.microsoft.com/en-us/azure/ai-services/containers/disconnected-containers |
| Orchestrate multiple Foundry containers with Docker Compose | https://learn.microsoft.com/en-us/azure/ai-services/containers/docker-compose-recipe |
> related_skills --same-repo
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> microsoft-foundry-local
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> microsoft-foundry-classic
Expert knowledge for Microsoft Foundry Classic (aka Azure AI Foundry classic) development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building Foundry agents with RAG, tools, evaluators, Azure OpenAI, VNet/Private Link, or CI/CD deployments, and other Microsoft Foundry Classic related development tasks. Not for Microsoft Foundry (use microsoft-foundry
> azure-static-web-apps
Expert knowledge for Azure Static Web Apps development including troubleshooting, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when wiring SWA APIs to Azure DBs, configuring custom domains/auth, CI/CD, preview slots, or Front Door/CDN, and other Azure Static Web Apps related development tasks. Not for Azure App Service (use azure-app-service), Azure Functions (use azure-functions), Azure Container Apps (use azure-container-apps),