Datasets Materialize Data Model

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

Annotations establish that this is a non-read-only, non-destructive, open-world operation, and the description adds key behavior beyond that: it creates a materialization job and returns it for polling. It does not describe idempotency, permissions, or side effects of re-running a scheduled materialization.

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?

The description is short, front-loaded with the primary action, and follows with the key parameter clarification and polling guidance. Every sentence carries useful 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 the description need not document return values in detail; mentioning that it returns a job and how to poll it is sufficient. The main gap is that data_model_id and the relationship to similar materialization siblings are not explained.

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 description coverage is 0%, so the description is needed to explain both required parameters. It explains that sheet_id is the element's ID, but data_model_id is left unexplained beyond its name, so it only partially compensates for the missing schema descriptions.

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?

The first sentence states a specific verb and resource: run the scheduled materialization for one data model element now. It clarifies what sheet_id represents, but it does not distinguish this tool from the similarly named sibling elements_materialize_element, so an agent must infer the difference.

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?

The description implies usage by saying 'run ... now' and routes the agent to datasets_get_data_model_materialization for polling. However, it gives no explicit when-to-use guidance, prerequisites, or exclusion versus elements_materialize_element or other materialization tools.

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