From azure
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 Analytics (use azure-synapse-analytics).
npx claudepluginhub atc-net/atc-agentic-toolkit --plugin azureThis skill uses the workspace's default tool permissions.
This skill provides expert guidance for Azure Cognitive 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.
Implements vector, hybrid, semantic search, indexing, and AI enrichment with Azure AI Search Python SDK. Covers authentication, clients, and vector field indexes.
Implements Azure AI Search Python SDK for vector, hybrid, full-text search, semantic ranking, indexing, document upload, and skillsets. Use for AI search and RAG apps.
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This skill provides expert guidance for Azure Cognitive 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.
IMPORTANT for Agent: This file may be large. Use the Category Index below to locate relevant sections, then use
read_filewith specific line ranges (e.g.,L136-L144) to read the sections needed for the user's question This skill requires network access to fetch documentation content. Usemcp_microsoftdocs:microsoft_docs_fetchto retrieve full articles.
WebFetch tool if the Microsoft Learn MCP server is not available.| Category | Lines | Description |
|---|---|---|
| Troubleshooting | L31-L41 | 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 | L43-L62 | 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 | L64-L74 | 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 | L76-L81 | Architectural guidance for Azure AI Search: RAG patterns, knowledge store design, multitenancy and tenant isolation, and multi-region/high-availability deployment designs. |
| Limits & Quotas | L83-L91 | 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 | L93-L131 | 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 | L133-L222 | Configuring Azure AI Search: data sources, indexes, analyzers, vector/semantic settings, skillsets/enrichment, knowledge bases, monitoring, and indexer/connection options. |
| Integrations & Coding Patterns | L224-L285 | 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 | L287-L294 | Deploying and moving Azure AI Search services: ARM/Bicep/Terraform provisioning, cross-region migration steps, and checking regional/feature availability. |
| 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 |
| 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 |
| 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 |
| 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 |