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model_instance_versions

List all versions of a model instance on Kaggle by providing the owner, model slug, framework, and instance slug.

Instructions

List all versions of a model instance.

    Args:
        owner: Model owner username.
        model_slug: Model slug/name.
        framework: Framework name (e.g. 'tensorflow2', 'pytorch', 'jax').
        instance_slug: Instance slug identifier.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ownerYes
model_slugYes
frameworkYes
instance_slugYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description bears the full burden of behavioral disclosure. However, it only states 'List all versions' without revealing any behavioral traits such as destructive potential, authentication needs, rate limits, or error handling. This is insufficient for a tool with no annotations.

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

Conciseness4/5

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

The description is concise: a single-line purpose followed by a parameter list. It is not overly verbose, and the essential information (purpose) is front-loaded. However, the parameter block feels redundant with the schema, slight inefficiency.

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

Completeness2/5

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

Despite having an output schema, the description does not mention any contextual details like ordering, pagination, or filtering of versions. For a list tool, these are important for correct invocation. The description is too minimal to be considered complete given the tool's complexity and 4 required parameters.

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

Parameters2/5

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

The schema has 0% description coverage, meaning no parameter descriptions in the schema. The description lists parameters and provides minimal explanations (e.g., 'owner: Model owner username') that essentially restate the parameter names. It adds little beyond what the parameter names already convey, failing to compensate for the schema's lack of detail.

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

Purpose5/5

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

The description clearly states 'List all versions of a model instance.' This directly specifies the action (list) and the resource (versions of a model instance), making the tool's purpose unambiguous. Among sibling tools like model_instance_create and model_instance_get, this one is distinctly for listing versions, so differentiation is clear.

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

Usage Guidelines3/5

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

The description does not provide any guidance on when to use this tool versus alternatives, nor does it mention prerequisites or context. The sibling list implies a context, but the description itself lacks explicit usage guidelines. It is adequate but missing this dimension.

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

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