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sdebruyn

fabric-dw-mcp-cli

by sdebruyn

transfer_table

Move a SQL table to a different schema in a Microsoft Fabric Data Warehouse. Permissions and dependent objects may need to be updated after transfer.

Instructions

Move a SQL table to another schema via ALTER SCHEMA ... TRANSFER OBJECT::....

Data-Warehouse-only: transferring a table between schemas via T-SQL is not supported on the Fabric SQL Analytics Endpoint and can break the OneLake sync, so SQL Analytics Endpoints are rejected with a ToolError.

CAUTION: Permissions granted directly on the table are dropped by the engine when the schema changes. Dependent views and stored procedures that reference the table by its old schema-qualified name are NOT automatically updated and may need refreshing after the transfer.

Args: workspace: Workspace name or GUID. item: Warehouse name or GUID. SQL Analytics Endpoints are rejected. qualified_name: Current dot-separated qualified table name, e.g. dbo.sales. target_schema: Schema to move the table into, e.g. archive.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemYes
workspaceYes
target_schemaYes
qualified_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the transparency burden, disclosing the specific SQL command, the rejection of unsupported endpoints, permission drops, and the need to refresh dependent objects—though it omits details on index/statistics handling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the purpose, followed by constraints, cautions, and parameter details—every sentence adds value with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (4 required params, no annotations), the description covers key aspects like purpose, constraints, and parameter examples, though it doesn't explicitly mention prerequisite checks like schema/table existence or output details (but output schema exists).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description provides clear explanations for all four parameters, including examples and the constraint on 'item' for SQL Analytics Endpoints, fully compensating for the lack of schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool moves a SQL table to another schema using ALTER SCHEMA ... TRANSFER, distinguishing it from siblings like rename_table, clone_table, or transfer_view.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description specifies it is Data-Warehouse-only and rejects SQL Analytics Endpoints, but does not explicitly contrast with other table operations like rename_table for schema changes or create_table+insert for copying.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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