Agent skill · software engineering · sickn33
azure-search-documents-dotnet
Azure AI Search SDK for .NET (Azure.Search.Documents). Use for building search applications with full-text, vector, semantic, and hybrid search.
Why this skill is useful
Provides specific commands and patterns for integrating Azure AI Search SDK with .NET applications that the AI may not reliably generate on its own.
What it needs
Requires dotnet installed locally. About 4k tokens when loaded. Last updated 2026-08-07. 44,571 stars on the source repository.
What this skill does
Bundled upstream support Supporting files are included at skill-relative paths. See UPSTREAM-NOTICE.md for their pinned sources, licenses, hashes, and import changes. Azure.Search.Documents (.NET) Build search applications with full-text, vector, semantic, and hybrid search capabilities. Installation Current Versions: Stable v11.7.0, Preview v11.8.0-beta.1 Environment Variables Authentication DefaultAzureCredential (preferred): API Key: Client Selection Client Purpose -------- --------- SearchClient Query indexes, upload/update/delete documents SearchIndexClient Create/manage indexes, synonym maps SearchIndexerClient Manage indexers, skillsets, data sources Index Creation Using FieldBuilder (Recommended) Manual Field Definition Document Operations Search Patterns Basic Search Faceted Search Autocomplete and Suggestions Vector Search See references/vector-search.md for detailed patterns. Semantic Search See references/semantic-search.md for detailed patterns. Hybrid Search (Vector + Keyword + Semantic) Field Attributes Reference Attribute Purpose ----------- --------- SimpleField Non-searchable field (filters, sorting, facets) SearchableField Full-text searchable field VectorSearchField Vector embedding field IsKey = true Document key (required, one per index) IsFilterable = true Enable $filter expressions IsSortable = true Enable $orderby IsFacetable = true Enable faceted navigation IsHidden = true Exclude from results AnalyzerName Specify text analyzer Error Handling Best Practices 1. Use DefaultAzureCredential over API keys for production 2. Use FieldBuilder with model attributes for type-safe index definitions 3. Use CreateOrUpdateIndexAsync for idempotent index creation 4. Batch document operations for better throughput 5. Use Select to return only needed fields 6. Configure semantic search for natural language queries 7. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills sickn33/azure-search-documents-dotnet