model_instance_create

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

With no annotations provided, the description must fully disclose behavioral traits. It only states that it creates an instance and lists parameters. It does not mention idempotency, authentication needs, rate limits, or whether creation might overwrite existing instances.

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 structured as a Python docstring with a purpose sentence followed by an Args list. It is concise and front-loaded, though the parameter list could be more compact.

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?

Although an output schema exists and return values are not required, the description misses important behavioral context for a creation tool, such as whether the operation is idempotent, if it triggers side effects, or how it interacts with other model operations.

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 must compensate. It provides brief explanations for each parameter, including examples for 'framework' and defaults for 'license_name' and 'is_private'. However, it largely repeats the schema and adds limited new meaning beyond parameter names.

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 clearly states 'Create a new instance for a Kaggle model,' which is a specific verb+resource combination. It differentiates from sibling tools like 'model_create' (creates the model itself) and 'model_instance_version_create' (creates a version of an instance).

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 provides no guidance on when to use this tool versus alternatives. It lacks information on prerequisites, when not to use it, or how it compares to related tools such as 'model_create' or 'model_instance_version_create'.

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