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sdebruyn

fabric-dw-mcp-cli

by sdebruyn

update_sql_pool

Modify an existing SQL pool by updating only the parameters you specify, such as resource percentage, default flag, read optimization, and classifier settings. Requires workspace admin role.

Instructions

Update an existing SQL pool. Only the parameters you supply are changed.

Args: workspace: Workspace name or GUID. name: Name of the pool to update. max_percent: New max resource percentage (1-100), or omit to keep current. is_default: Set or clear the default flag, or omit to keep current. optimize_for_reads: Enable/disable read optimisation, or omit to keep current. classifier_type: New classifier type, or omit to keep current. classifier_values: New classifier value list, or omit to keep current.

Requires workspace admin role. This tool targets a beta / preview API.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspaceYes
nameYes
max_percentNo
is_defaultNo
optimize_for_readsNo
classifier_typeNo
classifier_valuesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations are provided, but the description covers key behaviors: partial updates, admin role requirement, and API maturity (beta/preview). It does not describe output or error scenarios, but the output schema (present) covers return structure.

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 purpose, followed by a clearly formatted parameter list. Every sentence is informative, with no filler. It is concise yet comprehensive.

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 7 parameters, 2 required, and an output schema present, the description covers purpose, all parameter details, auth requirement, and API maturity. Missing details like failure modes or idempotency are acceptable given the output schema availability.

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 description coverage is 0%, so the description fully compensates by explaining each parameter's purpose, allowed values (e.g., max_percent range 1-100), and effect (e.g., 'Set or clear the default flag'). This adds critical meaning beyond the raw schema.

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 'Update an existing SQL pool.' and contrasts with create/delete siblings. The verb 'update' and resource 'SQL pool' are specific and distinct.

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 explains partial update behavior ('Only the parameters you supply are changed'), lists all parameters with their semantics, and notes admin role requirement and beta/preview status. It does not explicitly mention when not to use, but sibling tools cover creation/deletion.

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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