After the INSERT → SET @OrderId = SCOPE_IDENTITY()

Inside CATCH → IF @@TRANCOUNT > 0 ROLLBACK TRANSACTION

The correct drag-and-drop choices are:

SET @OrderId = SCOPE_IDENTITY()

IF @@TRANCOUNT > 0 ROLLBACK TRANSACTION

After the INSERT, the procedure should assign the newly generated identity value to the output parameter by using SCOPE_IDENTITY() . Microsoft documents that SCOPE_IDENTITY() returns the last identity value inserted in the same scope, which makes it the correct choice for returning the new OrderId from the procedure.

Inside the CATCH block, the procedure should use IF @@TRANCOUNT > 0 ROLLBACK TRANSACTION before THROW. This ensures any open transaction is rolled back only when one actually exists, which prevents transaction-state issues and guarantees the failure aborts the transaction cleanly. Keeping THROW after the rollback is also the correct modern pattern because THROW re-raises the error to the caller with the original error information intact, giving consistent error behavior. This matches SQL Server best practice for TRY...CATCH transaction handling.

The first correct selection is embedding because a vector index must be created on the vector column , not on a scalar distance column or a text column such as product_name. Microsoft’s CREATE VECTOR INDEX documentation shows that the index is created directly on the vector-valued column, for example ON product_embeddings(embedding).

The second correct selection is VECTOR_SEARCH because the requirement is to use a supplied natural language query vector and search against the indexed embeddings. Microsoft documents that VECTOR_SEARCH is the Transact-SQL function for approximate nearest neighbor vector retrieval and that it applies to SQL database in Microsoft Fabric as well as other supported SQL platforms.

This also matches the shown code pattern:

declare a vector variable such as @query_vector VECTOR(1536),

create a vector index on dbo.Products(embedding),

query with VECTOR_SEARCH(... SIMILAR_TO = @query_vector, METRIC = ' cosine ' , TOP_N = 10).

This does not meet the goal. A row-by-row DELETE against the oldest month is not the lowest-impact way to purge data from a monthly partitioned table. Microsoft’s partitioning guidance specifically says partitioning lets you perform maintenance and retention operations more efficiently by targeting just the relevant partition, including the ability to truncate data in a single partition .

The proposed statement:

DELETE FROM dbo.Orders

WHERE OrderDate < DATEADD(month, -36, SYSUTCDATETIME());

would log row deletions and can hold locks longer, creating more overhead for other queries than a partition-level maintenance operation. Since the table is already partitioned by month , the expected low-impact approach is to operate on the oldest partition directly, not issue a broad delete predicate over rows. Microsoft explicitly highlights partition-targeted truncation as a faster, more efficient retention operation than working against the whole table or rowset.

The first statement is No . GETDATE() is a nondeterministic built-in function, and SQL Server UDF guidance does not support using nondeterministic built-ins inside a T-SQL user-defined function for this purpose. Microsoft explicitly classifies GETDATE() as nondeterministic.

The second statement is Yes . Multi-statement TVFs are a common source of weak cardinality estimates and unstable plans because the optimizer has less information about their result sizes. Microsoft documents features such as interleaved execution for multi-statement TVFs , which exist specifically because MSTVFs have optimization challenges, and Microsoft also notes that scalar/UDF style constructs can lead to poorer optimization behavior than relationally inlined alternatives. Rewriting an MSTVF as an inline TVF generally gives the optimizer better visibility and more consistent plans.

The third statement is Yes . Scalar functions must be invoked using at least the two-part name < schema > . < function > . Microsoft’s documentation is explicit on that point for executing user-defined functions. So changing ufn_GetTaxMultiplier to dbo.ufn_GetTaxMultiplier resolves the naming error in the EXEC statement.

Yes, this meets the goal. Microsoft documents that on a partitioned table , you can use TRUNCATE TABLE ... WITH (PARTITIONS (...)) to remove data from a specific partition, and that this is an efficient maintenance operation that targets only that data subset rather than the whole table. Microsoft’s partitioning guidance explicitly lists truncating a single partition as an example of a fast partition-level maintenance or retention operation.

That matches the requirement to remove the oldest month while minimizing impact on other queries. Because the table is already partitioned by month on OrderDate , identifying the partition number for that oldest month and truncating only that partition is the correct low-impact approach, assuming the table and indexes are aligned as required for partition truncation.

The correct choice is Option A because it provides the relevant semantic context the LLM needs while avoiding an unnecessary field that would add tokens without improving answer quality.

For LLM grounding and RAG-style context, Microsoft guidance emphasizes mapping and sending the fields that contain text pertinent to the use case . In this FAQ scenario, the useful context is the ProductName , the Question , and the Answer . Those three fields help the model understand both the subject domain and the actual Q & A pair. By contrast, FaqId is just a technical identifier and generally adds no semantic value for response generation, so including it wastes tokens.

That is why Option A is better than the others:

Option A keeps the meaningful text fields and removes the low-value identifier.

Option B is too minimal because it includes only the answer text as Prompt, which strips away the product and question context the LLM may need for accurate grounding.

Option C keeps FaqId but omits ProductName, which can be important disambiguating context.

Option D includes everything, but that does not minimize token usage because it keeps the unnecessary FaqId.

The first statement is Yes . Embeddings are used to represent the semantic meaning of content, and vector search is for conceptually similar matches over that content. Here, the semantically meaningful fields are product_name, category, and description. Using those together supports natural-language search, while brand and price can be handled as structured filters outside the embedding itself. This is an inference from Microsoft’s guidance that vector search works over embeddings representing content meaning, while filters remain part of the nonvector query pipeline.

The second statement is No . price changes multiple times per day and is a structured numeric attribute, not stable semantic content. Since the requirement already says customers can apply structured filters for brand and price , price does not need to be embedded into the text. Embedding volatile numeric values would also make embeddings stale faster without improving the semantic-search objective. This is again an inference grounded in Microsoft’s distinction between vector similarity over content and filtering/sorting over nonvector fields.

The third statement is Yes . In SQL Server’s vector type, the default underlying base type is float32 unless float16 is specified explicitly.

GitHub documents that repository custom instructions for Copilot Chat can be disabled for your own use in the editor settings, and that doing so does not affect other users . In VS Code, this is controlled through settings related to instruction files, where you can disable the use of repository instruction files for your own environment.

The other options are incorrect:

B is not a documented mechanism for disabling repository-level Copilot instructions.

C would remove the repository instruction file itself and therefore affect everyone using that repository, which violates the requirement.