azure-cognitive-search

# 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 issues, including errors, warnings, OData filters, portal debug sessions, private link, and storage/metrics discrepancies |
| Best Practices | L49-L69 | Designing, scaling, and troubleshooting Azure AI Search indexing/query pipelines, including enrichment, data modeling, concurrency, cost/perf tuning, chunking, vectors, and handling blob/SQL changes. |
| Decision Making | L70-L83 | Guidance on planning and managing Azure AI Search services: pricing and tiers, capacity estimation and upgrades, regional choices, SDK/API migrations, and cost optimization. |
| Architecture & Design Patterns | L84-L90 | Architectural guidance for Azure AI Search: RAG patterns, knowledge store design, multitenancy and tenant isolation, and multi-region/high-availability deployment designs. |
| Limits & Quotas | L91-L100 | Limits, quotas, and scheduling for Azure AI Search: billing/free enrichment, indexer run windows and runtime caps, service/index/vector size limits by tier and platform. |
| Security | L101-L138 | Securing Azure AI Search: identity/RBAC, keys and encryption, private networking, indexer access to data sources, document-level ACLs, and policy/compliance controls. |
| Configuration | L139-L238 | Configuring Azure AI Search: data sources, indexers, indexes, analyzers, skills/enrichment, vectors, semantic ranker, monitoring, and agentic retrieval/answer synthesis settings. |
| Integrations & Coding Patterns | L239-L300 | Patterns and code for integrating Azure AI Search with data sources, indexers, vectorization, OData/Lucene queries, semantic ranking, custom skills, and knowledge stores/Power BI. |
| Deployment | L301-L307 | Deploying and moving Azure AI Search services with ARM/Bicep/Terraform, plus guidance on cross-region moves and checking regional feature and SKU availability. |

### Troubleshooting
| Topic | URL |
|-------|-----|
| Troubleshoot Azure AI Search indexer errors and warnings | https://learn.microsoft.com/en-us/azure/search/cognitive-search-common-errors-warnings |
| Understand Debug Sessions for skillset troubleshooting | https://learn.microsoft.com/en-us/azure/search/cognitive-search-debug-session |
| 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 |
| Troubleshoot Azure AI Search indexer issues without errors | https://learn.microsoft.com/en-us/azure/search/search-indexer-troubleshooting |
| Troubleshoot OData collection filter errors in Azure AI Search | 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 Azure AI Search storage and metric discrepancies | https://learn.microsoft.com/en-us/azure/search/troubleshoot-storage-metrics |

### Best Practices
| Topic | URL |
|-------|-----|
| Design tips and troubleshooting for AI enrichment pipelines | 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 |
| Model SQL relational data for Azure AI Search indexing | https://learn.microsoft.com/en-us/azure/search/index-sql-relational-data |
| 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-index-azure-blob-changed-deleted |
| Optimize Azure Blob plaintext indexing with parsing modes | https://learn.microsoft.com/en-us/azure/search/search-how-to-index-azure-blob-plaintext |
| Optimize large-scale indexing in Azure AI Search | https://learn.microsoft.com/en-us/azure/search/search-how-to-large-index |
| Model complex and nested data in Azure AI Search | https://learn.microsoft.com/en-us/azure/search/search-howto-complex-data-types |
| Apply optimistic concurrency for Azure AI Search resources | https://learn.microsoft.com/en-us/azure/search/search-howto-concurrency |
| Update or rebuild Azure AI Search indexes safely | https://learn.microsoft.com/en-us/azure/search/search-howto-reindex |
| Analyze Azure AI