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sdebruyn

fabric-dw-mcp-cli

by sdebruyn

update_view

Redefine a SQL view by running a CREATE OR ALTER VIEW statement with a read-only SELECT body, automatically rejecting write operations and semicolons for safety.

Instructions

Redefine a SQL view via CREATE OR ALTER VIEW.

CAUTION: select_body is executed verbatim as DDL. Ensure the body matches the user's intent before calling this tool.

select_body must be a single read-only SELECT or WITH (CTE) statement. The guard is always on and fail-closed: a write keyword (DELETE, DROP, INSERT, etc.) or a semicolon anywhere in the body is rejected, even inside a string literal or quoted identifier. If a legitimate view body contains a write keyword (e.g. a column alias 'DELETE'), rewrite the expression to avoid the keyword.

Args: workspace: Workspace name or GUID. item: Warehouse or SQL endpoint name or GUID. qualified_name: Dot-separated qualified view name, e.g. dbo.vw_sales. select_body: Single read-only SELECT or WITH (CTE) statement for the new view body. Write keywords and semicolons are rejected fail-closed, even inside string literals or quoted identifiers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemYes
workspaceYes
select_bodyYes
qualified_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

No annotations present, so the description fully carries the burden. It discloses that select_body is executed verbatim as DDL, describes the guard mechanism (fail-closed, rejecting write keywords and semicolons even in strings), and suggests rewrites for legitimate cases. 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?

The description is fairly long but every sentence serves a purpose. It is front-loaded with the main action and structured with clear sections. Could be slightly more concise, but it's well-organized.

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 that an output schema exists, return values are not needed. The description covers the tool's action, parameter constraints, and behavioral guard. It could mention permissions or side effects, but it is adequate for a complex DDL tool.

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 description coverage is 0%, so description must add meaning. It provides detailed semantics for select_body (the guard behavior). For workspace, item, and qualified_name, it adds minimal but sufficient context. Overall, significant value added for the critical parameter.

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 'Redefine a SQL view via CREATE OR ALTER VIEW.' This is specific and distinguishes it from sibling tools like create_view, drop_view, rename_view, etc.

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?

Provides guidance on when to use the tool, including constraints on select_body (must be read-only SELECT/WITH, no write keywords or semicolons). Does not explicitly state when not to use it, but the context is 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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