> azure-cognitive-search
Expert knowledge for Azure AI Search development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when designing indexes, skillsets, vector/semantic search, indexers, private endpoints, or RAG apps, and other Azure AI Search related development tasks. Not for Azure Cosmos DB (use azure-cosmos-db), Azure Data Explorer (use azure-data-explorer), Azure Synapse Ana
curl "https://skillshub.wtf/MicrosoftDocs/Agent-Skills/azure-cognitive-search?format=md"Azure AI Search Skill
This skill provides expert guidance for Azure AI Search. Covers troubleshooting, 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 |
|---|---|---|
| Troubleshooting | L37-L48 | Diagnosing and fixing Azure AI Search indexer/skillset issues, debug sessions, OData filter errors, and private link problems, including cases with warnings or no explicit errors. |
| Best Practices | L49-L69 | Best practices for indexing, enrichment, chunking, vectors, performance, concurrency, and safe updates in Azure AI Search, including RAG, custom skills, and responsible GenAI usage. |
| Decision Making | L70-L81 | Guidance on upgrading/migrating Azure AI Search skills/SDKs, estimating capacity, choosing pricing tiers, and planning costs and hardware for search workloads |
| Architecture & Design Patterns | L82-L88 | Architectural guidance for Azure AI Search: RAG patterns, knowledge store design, multitenancy and tenant isolation, and multi-region/high-availability deployment designs. |
| Limits & Quotas | L89-L98 | Limits, quotas, and behaviors for Azure AI Search services, indexers, enrichment, and vector indexes, plus a .NET tutorial that illustrates index size and loading constraints. |
| Security | L99-L138 | Securing Azure AI Search: auth (keys/RBAC), encryption (CMK), network isolation (firewalls, private endpoints), and indexer access to protected data with ACL/RBAC and Purview labels. |
| Configuration | L139-L229 | Configuring Azure AI Search: data sources, indexes, analyzers, vector/semantic settings, skillsets/enrichment, knowledge bases, monitoring, and indexer/connection options. |
| Integrations & Coding Patterns | L230-L292 | Patterns and code for integrating Azure AI Search with apps and data sources, building indexers, custom skills/vectorizers, OData/Lucene queries, semantic/agentic retrieval, and knowledge store/BI flows. |
| Deployment | L293-L300 | Deploying and moving Azure AI Search services: ARM/Bicep/Terraform provisioning, cross-region migration steps, and checking regional/feature availability. |
Troubleshooting
Best Practices
Decision Making
| Topic | URL |
|---|---|
| Migrate from deprecated Azure AI Search skills | https://learn.microsoft.com/en-us/azure/search/cognitive-search-skill-deprecated |
| Migrate Azure AI Search REST clients to newer API versions | https://learn.microsoft.com/en-us/azure/search/search-api-migration |
| Estimate Azure AI Search capacity for indexing and queries | https://learn.microsoft.com/en-us/azure/search/search-capacity-planning |
| Choose and use Azure AI Search management SDKs | https://learn.microsoft.com/en-us/azure/search/search-dotnet-mgmt-sdk-migration |
| Upgrade Azure AI Search .NET apps to SDK v11 | https://learn.microsoft.com/en-us/azure/search/search-dotnet-sdk-migration-version-11 |
| Upgrade Azure AI Search services to higher-capacity hardware | https://learn.microsoft.com/en-us/azure/search/search-how-to-upgrade |
| Plan and manage Azure AI Search costs | https://learn.microsoft.com/en-us/azure/search/search-sku-manage-costs |
| Choose the right Azure AI Search pricing tier | https://learn.microsoft.com/en-us/azure/search/search-sku-tier |
Architecture & Design Patterns
| Topic | URL |
|---|---|
| Apply RAG patterns with Azure AI Search and generative AI | https://learn.microsoft.com/en-us/azure/search/retrieval-augmented-generation-overview |
| Implement multitenancy and content isolation in Azure AI Search | https://learn.microsoft.com/en-us/azure/search/search-modeling-multitenant-saas-applications |
| Design multi-region architectures for Azure AI Search | https://learn.microsoft.com/en-us/azure/search/search-multi-region |
Limits & Quotas
| Topic | URL |
|---|---|
| Attach Foundry resource and understand AI enrichment quotas | https://learn.microsoft.com/en-us/azure/search/cognitive-search-attach-cognitive-services |
| Run and reset Azure AI Search indexers effectively | https://learn.microsoft.com/en-us/azure/search/search-howto-run-reset-indexers |
| Schedule Azure AI Search indexers and understand run windows | https://learn.microsoft.com/en-us/azure/search/search-howto-schedule-indexers |
| Azure AI Search service limits and quotas by tier | https://learn.microsoft.com/en-us/azure/search/search-limits-quotas-capacity |
| Create and load an index in .NET tutorial | https://learn.microsoft.com/en-us/azure/search/tutorial-csharp-create-load-index |
| Understand Azure AI Search vector index size limits | https://learn.microsoft.com/en-us/azure/search/vector-search-index-size |
Security
Configuration
Integrations & Coding Patterns
Deployment
| Topic | URL |
|---|---|
| Deploy Azure AI Search service using ARM templates | https://learn.microsoft.com/en-us/azure/search/search-get-started-arm |
| Deploy Azure AI Search service using Bicep | https://learn.microsoft.com/en-us/azure/search/search-get-started-bicep |
| Provision Azure AI Search with Terraform | https://learn.microsoft.com/en-us/azure/search/search-get-started-terraform |
| Manually move Azure AI Search services across regions | https://learn.microsoft.com/en-us/azure/search/search-howto-move-across-regions |
| Check Azure AI Search regional and feature availability | https://learn.microsoft.com/en-us/azure/search/search-region-support |
> 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