azuresql-db-rag Skill
Builds local vector search, RAG, embeddings, and semantic search on Azure SQL Developer using the native VECTOR type and VECTORDISTANCE. Use when you need to store embeddings, do similarity search, top-k nearest neighbor, cosine distance, retrieval-augmented generation, "find similar documents", chatbot memory, or sema Published by microsoft in azure-sql-database-container.
What is azuresql-db-rag Skill?
Builds local vector search, RAG, embeddings, and semantic search on Azure SQL Developer using the native VECTOR type and VECTORDISTANCE. Use when you need to store embeddings, do similarity search, top-k nearest neighbor, cosine distance, retrieval-augmented generation, "find similar documents", chatbot memory, or sema Published by microsoft in azure-sql-database-container. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Database workflows
- Deployment
- Design and media
- Research
- Database workflows use cases
Technical details
- Install or run with Copy skill directory
When to use azuresql-db-rag Skill
- Use it for database workflows.
- Use it for deployment.
- Use it for design and media.
- Use it for research.
Built with
Editorial notes
Source
- Creator: microsoft
- Repository: microsoft/azure-sql-database-container
- Skill file: skills/azuresql-db-rag/SKILL.md
What it does
Builds local vector search, RAG, embeddings, and semantic search on Azure SQL Developer using the native VECTOR type and VECTORDISTANCE. Use when you need to store embeddings, do similarity search, top-k nearest neighbor, cosine distance, retrieval-augmented generation, "find similar documents", chatbot memory, or sema
Skill instructions
Azure SQL Developer: local vector search and RAG Store embeddings and run similarity search directly in the Azure SQL Database engine using the native VECTOR(n) type and VECTORDISTANCE. No separate vector store needed. Identity (read this first) This targets the Azure SQL Database engine running locally in a container, NOT the SQL Server image. Confirm with: sql SELECT SERVERPROPERTY('EngineEdition'); -- 5 SELECT SERVERPROPERTY('Edition'); -- 'SQL Azure' If you were about to pull mcr.microsoft.com/mssql/server, stop: that is the wrong image. Use the image below instead. - Image: sqldbpreview-dpgaeqhmgphzd4bk.azurecr.io/azure-sql/db-dev:latest (x64, linux/amd64; private preview registry, sign in first with docker login sqldbpreview-dpgaeqhmgphzd4bk.azurecr.io). Registry and tag are provisional during Private Preview. - On a non-x64 host, add --platform linux/amd64. - For the full container lifecycle, readiness, and connection model, see the azuresql-db-container skill. The minimal facts
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Frequently asked questions
What is azuresql-db-rag?
azuresql-db-rag is a open-source AI agent skill with Copy skill directory. Builds local vector search, RAG, embeddings, and semantic search on Azure SQL Developer using the native VECTOR type and VECTORDISTANCE.
Who is azuresql-db-rag best for?
azuresql-db-rag is best for reusing agent instructions, scripts, and references, database workflows, deployment workflows, design and media workflows.
How do I install azuresql-db-rag?
Install or run azuresql-db-rag using Copy skill directory. Check azuresql-db-rag for the latest setup command.
Is azuresql-db-rag actively maintained?
azuresql-db-rag may need a closer maintenance check before production use.
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