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sdebruyn

fabric-dw-mcp-cli

by sdebruyn

delete_schema

Remove a SQL schema from a Microsoft Fabric warehouse or SQL Analytics Endpoint. Use cascade to delete all tables and views within the schema.

Instructions

Drop a SQL schema from a warehouse.

CAUTION: This is a destructive, irreversible operation. The schema will be permanently deleted. If the schema still contains tables or views, the operation will fail unless cascade is True.

CAUTION: When cascade is True, all tables and views in the schema are permanently deleted along with their data. Confirm explicitly with the user before calling with cascade=True.

Both Fabric Data Warehouses and SQL Analytics Endpoints support DROP SCHEMA per the Microsoft Fabric T-SQL reference.

Args: workspace: Workspace name or GUID. item: Warehouse or SQL Analytics Endpoint name or GUID. name: The schema name to drop. cascade: When True, drop all tables and views in the schema first. Defaults to False.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspaceYes
itemYes
nameYes
cascadeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations provided, so description carries full burden. It discloses destructive operation, failure condition without cascade, and cascade behavior deleting all tables/views. This is thorough.

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

Conciseness4/5

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

Well-structured with main description, two caution blocks, and Args list. Front-loaded with purpose. While slightly lengthy, every sentence adds value. Could be slightly more concise but not wasteful.

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 it's a destructive operation with an output schema (not shown), the description explains behavior well. It covers failure conditions and cascade implications, though return values and error details are not mentioned.

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

Parameters4/5

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

Schema coverage is 0%, but description includes an Args section explaining each parameter (workspace, item, name, cascade) with context, adding significant meaning beyond the schema's basic titles and types.

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

Purpose4/5

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

The description clearly states 'Drop a SQL schema from a warehouse' with a specific verb and resource. While it doesn't explicitly differentiate from siblings like create_schema, the purpose is unambiguous.

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 includes explicit cautions about destructive and irreversible nature, and instructs to confirm with user before calling with cascade=True. This provides clear guidance on when to use and seek confirmation.

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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