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sdebruyn

fabric-dw-mcp-cli

by sdebruyn

drop_function

Drop a T-SQL user-defined function in Microsoft Fabric Data Warehouses or SQL Analytics Endpoints. Optionally use IF EXISTS to avoid errors when function does not exist.

Instructions

Drop a T-SQL user-defined function.

Function DDL is supported on both Data Warehouses and SQL Analytics Endpoints.

Args: workspace: Workspace name or GUID. item: Warehouse or SQL Analytics Endpoint name or GUID. qualified_name: Dot-separated qualified function name, e.g. dbo.fn_clean_input. if_exists: When true, emits DROP FUNCTION IF EXISTS (no-op when function does not exist). Defaults to false.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspaceYes
itemYes
qualified_nameYes
if_existsNo

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 explains the if_exists parameter's behavior: 'When true, emits DROP FUNCTION IF EXISTS (no-op when function does not exist).' This is good transparency. It could be more explicit about irreversible deletion, but the qualification 'drop' implies destructive action.

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 concise, front-loading the purpose in the first sentence. Additional details are provided in a structured list format with no unnecessary words.

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 tool has 4 parameters, no annotations, and an output schema exists, the description adequately covers parameter meanings and behavior. It does not explain return values, but the output schema likely handles that. For a DROP operation, the description is sufficient.

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%, so the description must add meaning. It explains each parameter: workspace (Workspace name or GUID), item (Warehouse or SQL Analytics Endpoint name or GUID), qualified_name (with example 'dbo.fn_clean_input'), and if_exists (behavior and default). This adds significant value beyond the schema titles.

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 'Drop a T-SQL user-defined function.' It uses a specific verb ('Drop') and resource ('T-SQL user-defined function'), and distinguishes itself from sibling tools like drop_procedure and drop_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 notes that function DDL is supported on Data Warehouses and SQL Analytics Endpoints, providing context on where the tool applies. It does not explicitly state when to use vs alternatives, but the sibling tools for procedures and views make it clear.

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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