Datasets Create Data Model

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

Annotations already declare readOnly=false, destructive=false, and openWorld=true, so the lower bar applies. The description adds useful payload-shape context (the spec must contain name, folderId, schemaVersion, and pages with elements), but says nothing about validation failures, permission requirements, or whether the call is idempotent.

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

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

Two tight sentences, zero filler, with the action stated first and the payload contract immediately after. Nothing could be removed without losing information.

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

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

An output schema exists, so return values need no explanation, and the required top-level spec fields are covered. However, for a nested, free-form JSON payload the description does not explain the shape of pages/elements or what a valid schemaVersion looks like, leaving meaningful gaps for a tool whose only input is an untyped object.

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

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

Schema coverage is 0% and the single parameter is an opaque 'object' with additionalProperties=true, so the description does real work by enumerating the required top-level keys (name, folderId, schemaVersion, pages/elements). It stops short of describing element structure or accepted value formats, but it substantially compensates for the empty schema.

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

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

States a specific verb and resource ('Create a data model from a JSON code representation'), which is unambiguous on its own. It does not, however, distinguish itself from siblings like datasets_update_data_model, datasets_get_data_model_spec, or workbooks_create_workbook, so an agent gets no routing signal.

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

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

There is no when-to-use guidance, no prerequisites, and no mention of alternatives such as datasets_update_data_model for modifying an existing model. The agent is left to infer that this is the creation path from the name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.