> azure-ai-services

Expert knowledge for Azure AI services development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building, debugging, or optimizing Azure AI services applications. Not for Azure AI Vision (use azure-ai-vision), Azure AI Anomaly Detector (use azure-anomaly-detector), Azure AI Search (use azure-cognitive-search), Azure Machine Learning (use azure-machine-learning).

fetch
$curl "https://skillshub.wtf/MicrosoftDocs/Agent-Skills/azure-ai-services?format=md"
SKILL.mdazure-ai-services

Azure AI services Skill

This skill provides expert guidance for Azure AI services. Covers troubleshooting, best practices, decision making, 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), 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
TroubleshootingL36-L40Diagnosing and fixing common Content Understanding issues, including model errors, data ingestion problems, configuration mistakes, and troubleshooting steps for failed analyses.
Best PracticesL41-L46Best practices for Azure AI Content Understanding: designing extraction workflows, tuning models, improving document parsing accuracy, and handling complex or low‑quality documents.
Decision MakingL47-L56Guidance on choosing pricing tiers and tools (Foundry vs Content Understanding vs Document Intelligence/LLMs), standard vs pro modes, migration steps, and estimating Content Understanding costs.
Limits & QuotasL57-L64Rate limits, quotas, and scaling for Foundry and Content Moderator/Understanding: autoscale strategies, image/term list limits, and how to stay within service quotas.
SecurityL65-L80Securing Azure AI/Foundry: auth (Entra, keys, Key Vault), encryption (CMK, data-at-rest), DLP for outbound calls, VNet rules, policy-based governance, and secure analyzer access.
ConfigurationL81-L99Configuring Foundry endpoints, credentials, containers, logging, and Content Understanding analyzers (classification, layout, audiovisual), routing, outputs, and resource recovery/purge.
Integrations & Coding PatternsL100-L109Using Azure Content Moderator and Content Understanding via REST/.NET: text/image/video moderation, custom term lists, and building custom multimodal analyzers and workflows.
DeploymentL110-L117How to package and run Foundry tools/containers on Azure (ACI, Docker Compose, disconnected), and deploy Foundry resources using Azure AI containers and ARM templates

Troubleshooting

TopicURL
Resolve common issues with Content Understandinghttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/faq

Best Practices

TopicURL
Apply best practices for Content Understanding workloadshttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/best-practices
Improve Content Understanding document extraction qualityhttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/document/analyzer-improvement

Decision Making

TopicURL
Choose and use Foundry commitment tier pricinghttps://learn.microsoft.com/en-us/azure/ai-services/commitment-tier
Choose between Content Understanding, Document Intelligence, and LLMshttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/choosing-right-ai-tool
Choose between standard and pro modes in Content Understandinghttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/standard-pro-modes
Choose between Foundry and Content Understanding Studiohttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/foundry-vs-content-understanding-studio
Migrate Content Understanding analyzers from preview to GAhttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/migration-preview-to-ga
Estimate and plan costs for Content Understandinghttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/pricing-explainer

Limits & Quotas

TopicURL
Use autoscale to increase Foundry rate limitshttps://learn.microsoft.com/en-us/azure/ai-services/autoscale
Use Content Moderator image lists within quota limitshttps://learn.microsoft.com/en-us/azure/ai-services/content-moderator/image-lists-quickstart-dotnet
Understand Content Moderator image and term list limitshttps://learn.microsoft.com/en-us/azure/ai-services/content-moderator/samples-dotnet
Review Content Understanding service quotas and limitshttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/service-limits

Security

TopicURL
Configure authentication for Foundry Tools requestshttps://learn.microsoft.com/en-us/azure/ai-services/authentication
Configure data loss prevention for Foundry outbound callshttps://learn.microsoft.com/en-us/azure/ai-services/cognitive-services-data-loss-prevention
Secure Foundry resources with virtual network ruleshttps://learn.microsoft.com/en-us/azure/ai-services/cognitive-services-virtual-networks
Understand Content Moderator data-at-rest encryption behaviorhttps://learn.microsoft.com/en-us/azure/ai-services/content-moderator/encrypt-data-at-rest
Configure secure access for Content Understanding analyzershttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/secure-communications
Enforce Entra-only auth by disabling local keyshttps://learn.microsoft.com/en-us/azure/ai-services/disable-local-auth
Configure customer-managed encryption keys for Foundryhttps://learn.microsoft.com/en-us/azure/ai-services/encryption/cognitive-services-encryption-keys-portal
Use built-in Azure Policies for Foundry governancehttps://learn.microsoft.com/en-us/azure/ai-services/policy-reference
Rotate Foundry API keys without downtimehttps://learn.microsoft.com/en-us/azure/ai-services/rotate-keys
Apply Azure Policy compliance controls to Foundryhttps://learn.microsoft.com/en-us/azure/ai-services/security-controls-policy
Apply security features for Foundry Tools resourceshttps://learn.microsoft.com/en-us/azure/ai-services/security-features
Secure Foundry applications using Azure Key Vaulthttps://learn.microsoft.com/en-us/azure/ai-services/use-key-vault

Configuration

TopicURL
Configure custom subdomains for Foundry endpointshttps://learn.microsoft.com/en-us/azure/ai-services/cognitive-services-custom-subdomains
Use environment variables for Foundry credentialshttps://learn.microsoft.com/en-us/azure/ai-services/cognitive-services-environment-variables
Create reusable Azure AI container images with presetshttps://learn.microsoft.com/en-us/azure/ai-services/containers/container-reuse-recipe
Configure Content Understanding analyzers and parametershttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/analyzer-reference
Configure classification and splitting in Content Understandinghttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/classifier
Connect Content Understanding analyzers to Foundry model deploymentshttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/models-deployments
Use and customize Content Understanding prebuilt analyzershttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/prebuilt-analyzers
Configure document layout and data extraction with Content Understandinghttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/document/elements
Interpret Content Understanding document Markdown outputhttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/document/markdown
Configure classification and routing in Content Understanding Studiohttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/classification-content-understanding-studio
Copy Content Understanding custom analyzers across resourceshttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/copy-analyzers
Configure audiovisual analysis for audio and video inputshttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/video/elements
Interpret audiovisual Markdown output from Content Understandinghttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/video/markdown
Configure diagnostic logging for Foundry resourceshttps://learn.microsoft.com/en-us/azure/ai-services/diagnostic-logging
Recover or purge deleted Foundry resourceshttps://learn.microsoft.com/en-us/azure/ai-services/recover-purge-resources

Integrations & Coding Patterns

TopicURL
Reference for Azure Content Moderator REST APIshttps://learn.microsoft.com/en-us/azure/ai-services/content-moderator/api-reference
Call Content Moderator image moderation APIshttps://learn.microsoft.com/en-us/azure/ai-services/content-moderator/image-moderation-api
Use custom term lists with Content Moderator .NET SDKhttps://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
Integrate Content Moderator video scanning in .NEThttps://learn.microsoft.com/en-us/azure/ai-services/content-moderator/video-moderation-api
Create custom Content Understanding analyzers via RESThttps://learn.microsoft.com/en-us/azure/ai-services/content-understanding/tutorial/create-custom-analyzer

Deployment

TopicURL
Run Foundry Tools using Azure AI containershttps://learn.microsoft.com/en-us/azure/ai-services/cognitive-services-container-support
Deploy Foundry containers to Azure Container Instanceshttps://learn.microsoft.com/en-us/azure/ai-services/containers/azure-container-instance-recipe
Run Foundry containers in disconnected environmentshttps://learn.microsoft.com/en-us/azure/ai-services/containers/disconnected-containers
Deploy multiple Azure AI containers with Docker Composehttps://learn.microsoft.com/en-us/azure/ai-services/containers/docker-compose-recipe
Deploy Foundry resources using ARM templateshttps://learn.microsoft.com/en-us/azure/ai-services/create-account-resource-manager-template

> related_skills --same-repo

> microsoft-foundry

Expert knowledge for Microsoft Foundry (aka Azure AI Foundry) 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 Azure OpenAI, vector search/RAG, Sora video, realtime audio, or MCP/LangChain APIs, and other Microsoft Foundry related development tasks. Not for Microsoft Foundry Classic (use microsoft-foundry-classic),

> 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

> microsoft-foundry-local

Expert knowledge for Microsoft Foundry Local (aka Azure AI Foundry Local) development including troubleshooting, best practices, decision making, configuration, and integrations & coding patterns. Use when using Foundry Local CLI, chat/transcription APIs, tools, OpenAI/LangChain clients, or upgrading legacy SDKs, and other Microsoft Foundry Local related development tasks. Not for Microsoft Foundry (use microsoft-foundry), Microsoft Foundry Classic (use microsoft-foundry-classic), Microsoft Foun

> 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

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first seenMar 17, 2026
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MicrosoftDocs/Agent-Skills
by MicrosoftDocs
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