> 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).
curl "https://skillshub.wtf/MicrosoftDocs/Agent-Skills/azure-ai-services?format=md"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), 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 |
|---|---|---|
| Troubleshooting | L36-L40 | Diagnosing and fixing common Content Understanding issues, including model errors, data ingestion problems, configuration mistakes, and troubleshooting steps for failed analyses. |
| Best Practices | L41-L46 | Best practices for Azure AI Content Understanding: designing extraction workflows, tuning models, improving document parsing accuracy, and handling complex or low‑quality documents. |
| Decision Making | L47-L56 | Guidance 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 & Quotas | L57-L64 | Rate limits, quotas, and scaling for Foundry and Content Moderator/Understanding: autoscale strategies, image/term list limits, and how to stay within service quotas. |
| Security | L65-L80 | Securing 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. |
| Configuration | L81-L99 | Configuring Foundry endpoints, credentials, containers, logging, and Content Understanding analyzers (classification, layout, audiovisual), routing, outputs, and resource recovery/purge. |
| Integrations & Coding Patterns | L100-L109 | Using Azure Content Moderator and Content Understanding via REST/.NET: text/image/video moderation, custom term lists, and building custom multimodal analyzers and workflows. |
| Deployment | L110-L117 | How 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
| Topic | URL |
|---|---|
| Resolve common issues with Content Understanding | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/faq |
Best Practices
| Topic | URL |
|---|---|
| Apply best practices for Content Understanding workloads | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/best-practices |
| Improve Content Understanding document extraction quality | 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 between Content Understanding, Document Intelligence, and LLMs | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/choosing-right-ai-tool |
| Choose between standard and pro modes in Content Understanding | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/standard-pro-modes |
| Choose between Foundry and Content Understanding Studio | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/foundry-vs-content-understanding-studio |
| Migrate Content Understanding analyzers from preview to GA | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/migration-preview-to-ga |
| Estimate and plan costs for Content Understanding | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/pricing-explainer |
Limits & Quotas
| Topic | URL |
|---|---|
| Use autoscale to increase Foundry rate limits | 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 |
| Understand Content Moderator image and term list limits | https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/samples-dotnet |
| Review Content Understanding service quotas and limits | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/service-limits |
Security
Configuration
Integrations & Coding Patterns
| Topic | URL |
|---|---|
| Reference for Azure Content Moderator REST APIs | https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/api-reference |
| Call Content Moderator image moderation APIs | https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/image-moderation-api |
| Use custom term lists with Content Moderator .NET SDK | 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 |
| Integrate Content Moderator video scanning in .NET | https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/video-moderation-api |
| Create custom Content Understanding analyzers via REST | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/tutorial/create-custom-analyzer |
Deployment
| Topic | URL |
|---|---|
| Run 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 |
| Deploy multiple Azure AI containers with Docker Compose | https://learn.microsoft.com/en-us/azure/ai-services/containers/docker-compose-recipe |
| Deploy Foundry resources using ARM templates | https://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