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notebook_create

Creates a new notebook in a Microsoft Fabric workspace using workspace ID, display name, and description. Enables AI assistants to provision notebooks for data engineering and analytics workflows.

Instructions

Create a new notebook in a workspace (long-running operation)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
descriptionNoDescription of the notebook
displayNameYesDisplay name for the notebook
workspaceIdYesThe workspace ID

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv2.8.0

TDQS

A3.7/5.0
Behavior4/5

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

The parenthetical 'long-running operation' is a valuable behavioral disclosure beyond the annotations, signaling that the call may not complete synchronously and may require polling or status checks. This adds meaningful context that the readOnlyHint and destructiveHint annotations do not provide.

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 a single, front-loaded sentence that states the core purpose and the key behavioral caveat. There is no wasted text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a long-running create operation with no output schema, the description does not explain what the caller receives (e.g., an operation ID) or how to track completion. This is a meaningful gap, though the required parameters and purpose are clear enough to invoke the tool.

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

Parameters3/5

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

Schema description coverage is 100%, so the parameters are already well documented in the schema. The description adds no additional parameter-level meaning, but it does not need to because the schema carries the full load.

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 states a specific verb ('Create'), a clear resource ('notebook'), and a location ('in a workspace'), making it immediately obvious what the tool does. It is distinct from sibling operations like notebook_update, notebook_delete, and notebook_list.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit guidance on when to use this tool versus alternatives, nor prerequisites such as ensuring the workspace exists. The usage is only implied by the verb 'create' and the resource name.

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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