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sdebruyn

fabric-dw-mcp-cli

by sdebruyn

create_sql_pool

Add a custom SQL pool to a Microsoft Fabric workspace. Configure resource percentage, default pool, read optimization, and classifier rules for workload management.

Instructions

Add a new custom SQL pool to a workspace.

Args: workspace: Workspace name or GUID. name: Pool name (must be unique within the workspace). max_percent: Max resource percentage (1-100). is_default: Whether this pool is the default pool. Defaults to false. optimize_for_reads: Enable read optimisation. Defaults to true. classifier_type: Classifier type (e.g. "Application Name"). classifier_values: List of classifier values (e.g. application names).

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspaceYes
nameYes
max_percentYes
is_defaultNo
optimize_for_readsNo
classifier_typeNo
classifier_valuesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the admin requirement and beta status but does not detail side effects, idempotency, or error behavior (e.g., what happens if pool name already exists).

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 and well-structured, with a clear list of arguments. Every sentence adds value without 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?

The description covers parameters and prerequisites adequately, but it does not describe the output schema or return value. Given the tool has an output schema, mentioning what the tool returns would improve completeness.

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?

The description lists each parameter in the Args section with explanations (e.g., 'name: Pool name (must be unique within the workspace)'). Since the input schema has no descriptions (coverage 0%), the description adds significant meaning beyond the 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 'Add a new custom SQL pool to a workspace.' It uses a specific verb ('add') and resource ('custom SQL pool'), distinguishing it from siblings like update_sql_pool and delete_sql_pool.

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 mentions a prerequisite ('Requires workspace admin role') and notes the tool targets a beta API. It does not explicitly state when to use versus alternatives, but the context of creation is clear given sibling tools.

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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