list_models

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

With no annotations, the description carries the full burden of behavioral disclosure, but it only says 'list / search.' It does not mention pagination, result shape, authentication needs, defaults, or whether filtering is server-side. The verb implies a safe read operation, but little else is revealed.

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 concise and front-loaded, with no wasted words. However, it is closer to a label than a structured explanation: it lacks any breakdown of parameters, defaults, return values, or usage context.

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?

For a tool with four undocumented optional parameters, zero annotations, no output schema, and many closely related model tools in the sibling list, this description is far too thin. It leaves the agent guessing how to form valid queries, what defaults apply, and what the response will look like.

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 all four parameters have empty descriptions. The description does not explain limit, owner, search, or sort_by beyond the general word 'search,' so an agent cannot determine how to construct a correct request or interpret parameter behavior.

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 uses a specific verb ('list / search') and identifies the resource ('Kaggle models'), so an agent can tell this is a discovery/read operation rather than create, update, or delete. It does not explicitly distinguish itself from sibling tools like list_model_instances or model_details, but the object 'models' is clear enough.

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?

No guidance is given on when to choose list_models over alternatives such as model_details, list_model_instances, or search_kernels. The phrase only implies the obvious use case—wanting to list or search models—without exclusions, prerequisites, or alternative routing.

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