/azure-cognitive-search

name: azure-cognitive-search
description: 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, indexers, vector/semantic search, or secure data source access, and other Azure AI Search related development tasks. Not for Azure Cosmos DB (use azure-cosmos-db), Azure SQL Database (use azure-sql-database), Azure Table Storage (use azure-table-storage), Azure Open Datasets (use azure-open-datasets).
compatibility: Requires network access. Uses mcp_microsoftdocs:microsoft_docs_fetch or fetch_webpage to retrieve documentation.
metadata:
  generated_at: "2026-09-06"
  generator: "docs2skills/1.0.0"

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`), 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](https://github.com/MicrosoftDocs/mcp/blob/main/README.md)

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

| Category | Lines | Description | |----------|-------|-------------| | Troubleshooting | L37-L48 | Diagnosing and fixing Azure AI Search indexer, skillset, filter, storage, metric, private link, and SharePoint permission issues, including portal-based debugging steps. | | Best Practices | L49-L66 | Designing, scaling, and troubleshooting enrichment and indexing pipelines, handling data changes, optimizing performance, vectors, costs, and applying safe, responsible AI and concurrency practices. | | Decision Making | L67-L82 | Guidance on choosing Azure AI Search tiers, pricing and regions, estimating capacity, handling limits, and migrating APIs/SDKs, skills, and agentic retrieval to newer versions. | | Architecture & Design Patterns | L83-L88 | Architectural patterns for Azure AI Search: combining vector and keyword search, designing multitenant or isolated indexes, and building resilient multi-region search deployments. | | Limits & Quotas | L89-L98 | Limits, quotas, and scheduling for indexers and enrichment, including billing/free tiers, runtime and concurrency caps, service capacity planning, and vector index size/scale constraints. | | Security | L99-L139 | Securing Azure AI Search: RBAC/Entra auth, keys, encryption, firewalls, private endpoints, and indexer access/ACLs for Storage, SQL, SharePoint, Cosmos DB, and Purview. | | Configuration | L140-L231 | Configuring Azure AI Search: data sources, index schemas, enrichment skillsets, analyzers, vectorization, semantic ranking, retrieval behavior, logging, and query options. | | Integrations & Coding Patterns | L232-L309 | Integrating Azure AI Search with apps and data sources, configuring indexers, skills, vectorization, semantic ranking, and query patterns (REST/SDK/MCP, OData/Lucene, hybrid/vector search). | | Deployment | L310-L317 | Deploying and moving Azure AI Search: ARM/Bicep/Terraform provisioning, cross-region migration, and deploying C# search apps to Azure Container Apps. |

Troubleshooting

| Topic | URL | |-------|-----| | Troubleshoot Azure AI Search indexer errors and warnings | https://learn.microsoft.com/en-us/azure/search/cognitive-search-common-errors-warnings | | Debug and troubleshoot Azure AI Search skillsets | https://learn.microsoft.com/en-us/azure/search/cognitive-search-how-to-debug-skillset | | Debug Azure AI Search skillsets using portal sessions | https://learn.microsoft.com/en-us/azure/search/cognitive-search-tutorial-debug-sessions | | Diagnose and fix Azure AI Search indexer issues | https://learn.microsoft.com/en-us/azure/search/search-indexer-troubleshooting | | Diagnose and fix Azure AI Search collection filter errors | https://learn.microsoft.com/en-us/azure/search/search-query-troubleshoot-collection-filters | | Troubleshoot shared private link resource issues in Azure AI Search | https://learn.microsoft.com/en-us/azure/search/troubleshoot-shared-private-link-resources | | Troubleshoot SharePoint permission-filtered queries in Azure AI Search | https://learn.microsoft.com/en-us/azure/search/troubleshoot-sharepoint-query-permission-filtering | | Diagnose Azure AI Search storage and metric discrepancies | https://learn.microsoft.com/en-us/azure/search/troubleshoot-storage-metrics |

Best Practices

| Topic | URL | |-------|-----| | Design and troubleshoot AI enrichment pipelines in Azure AI Search | https://learn.microsoft.com/en-us/azure/search/cognitive-search-concept-troubleshooting | | Scale and manage custom skills in Azure AI Search | https://learn.microsoft.com/en-us/azure/search/cognitive-search-custom-skill-scale | | Apply responsible AI best practices for GenAI Prompt skill | https://learn.microsoft.com/en-us/azure/search/responsible-ai-best-practices-genai-prompt-skill | | Handle changed and deleted blobs in Azure AI Search | https://learn.microsoft.com/en-us/azure/search/search-how-to-in