list_dataset_items

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states 'List items in a dataset' and does not mention pagination defaults, project scoping, read-only behavior, or any other operational traits beyond what the tool name implies.

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 a single, front-loaded sentence with no redundant words. It is appropriately concise for the tool's basic purpose, even though other dimensions reveal gaps in completeness.

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?

Despite the existence of an output schema, the description does not explain pagination parameters, project scope, or how it fits among sibling tools. With four parameters and no annotations, the description is too minimal to be fully contextual for an AI agent.

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% and the description provides no meaning for the parameters page, limit, project, or dataset_name. The only hint is 'dataset' which maps loosely to dataset_name, but it adds no value beyond the input schema itself.

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 description 'List items in a dataset' uses a specific verb ('List') and resource ('items in a dataset'), clearly distinguishing it from siblings like list_datasets (lists datasets) and get_dataset_item (retrieves a single item).

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 for enumerating items within a dataset, but it does not provide explicit guidance on when to use this tool versus alternatives such as get_dataset_item or list_datasets, nor does it mention any exclusions.

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