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list_models

Retrieve available image, video, and audio generation models with their type and pricing information for selection.

Instructions

List all available models for image, video, and audio generation with their type and pricing

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handleListModels function retrieves models by type and returns a formatted text output listing image, video, and audio models.
    export function handleListModels() {
      const imageModels = getModelsByType("image");
      const videoModels = getModelsByType("video");
      const audioModels = getModelsByType("audio");
    
      const formatModel = (m: (typeof models)[0]) => {
        let line = `  ${m.id} — ${m.name} [${m.free ? "FREE" : "PAID"}]`;
        if (m.price) line += ` (${m.price})`;
        if (m.description) line += ` — ${m.description}`;
        return line;
      };
    
      const text = [
        `IMAGE MODELS (${imageModels.length}):`,
        ...imageModels.map(formatModel),
        "",
        `VIDEO MODELS (${videoModels.length}):`,
        ...videoModels.map(formatModel),
        "",
        `AUDIO MODELS (${audioModels.length}):`,
        ...audioModels.map(formatModel),
      ].join("\n");
    
      return { content: [{ type: "text" as const, text }] };
    }
  • The listModelsSchema definition for the list_models tool.
    export const listModelsSchema = z.object({});
Behavior2/5

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 states the tool lists models with type and pricing, implying a read-only operation, but doesn't clarify aspects like whether it requires authentication, has rate limits, returns paginated results, or includes metadata beyond type and pricing. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 a single, well-structured sentence that directly conveys the tool's purpose without any wasted words. It is front-loaded with the core action ('List all available models') and includes essential details ('for image, video, and audio generation with their type and pricing'), making it highly efficient and easy to parse.

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

Completeness3/5

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

Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is minimally adequate. It explains what the tool does but lacks behavioral details like authentication needs or output format. Without annotations or an output schema, the description should ideally cover more about the return values and operational context, but it meets the basic requirement for a simple listing tool.

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?

The tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it appropriately avoids discussing inputs. A baseline of 4 is applied for zero-parameter tools, as it efficiently handles the lack of inputs without unnecessary detail.

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: 'List all available models for image, video, and audio generation with their type and pricing.' It specifies the verb ('List'), resource ('available models'), and scope ('image, video, and audio generation'). However, it doesn't explicitly differentiate from sibling tools like 'list_styles' or 'build_prompt,' which prevents a perfect score.

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 prerequisites, such as needing to check models before generating content, or compare it to siblings like 'list_styles' for style options. Without any usage context, the agent must infer when this tool is appropriate.

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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