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get_model_version

Read-onlyIdempotent

Retrieve detailed information about a specific model version on Civitai, including download URLs, trigger words, base model specifications, files, and example images.

Instructions

Get details about a specific model version by version ID.

Returns: download URLs, trigger words, base model, files, example images.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
version_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, covering safety and idempotency. The description adds value by listing return details ('download URLs, trigger words, base model, files, example images'), which helps anticipate output. However, it doesn't disclose additional behavioral traits like rate limits, auth needs, or error conditions beyond what annotations provide.

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

Conciseness5/5

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

The description is front-loaded with the core purpose in the first sentence, followed by a concise list of return details. Both sentences earn their place by providing essential information without waste. It's appropriately sized for a simple lookup tool.

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

Completeness4/5

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

Given the tool's low complexity (one parameter), rich annotations, and presence of an output schema, the description is mostly complete. It covers the purpose and return details, though it lacks usage guidelines. The output schema likely documents return values, so the description doesn't need to explain them in depth, but more context on when to use this tool would improve completeness.

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

Parameters4/5

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

Schema description coverage is 0%, with one parameter 'version_id' of type integer, but the description compensates by explaining its role: 'by version ID.' This adds semantic meaning beyond the schema, clarifying that 'version_id' identifies a specific model version. Since there's only one parameter, the description effectively covers it, earning a baseline 4.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Get details about a specific model version by version ID.' It specifies the verb ('Get details'), resource ('model version'), and key identifier ('version ID'). However, it doesn't explicitly differentiate from sibling tools like 'get_model_version_by_hash' or 'get_model_version_mini', which likely serve similar purposes with different identifiers or detail levels.

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

Usage Guidelines2/5

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 doesn't mention sibling tools such as 'get_model_version_by_hash' (which might use a hash instead of ID) or 'get_model_version_mini' (which might return less detail), nor does it specify prerequisites or exclusions. Usage is implied by the purpose but lacks explicit context.

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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