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ViewMax MCP

List video models

list_video_models

Every video model on offer with its exact limits and credit prices: which lengths, resolutions and frame shapes it accepts, whether it renders audio, how long it takes, and what a second of output costs. Use it to choose a model on price or capability, or to quote a cost before rendering.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses that the tool returns a list of all video models with their limits and credit prices, and that it is a read-only informational operation. It doesn't explicitly state that it makes no changes, but the verb 'list' and the content described make the read-only nature clear. It could add a note about no side effects, but the description is quite transparent.

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?

Two sentences, front-loaded with the core purpose and the exact data returned, followed by concrete use cases. Every sentence earns its place; no filler or repetition of the title.

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?

For a zero-parameter list tool with no output schema, the description is nearly complete. It tells the agent what data is returned and when to use it. The only minor gap is that it doesn't specify the response format (e.g., array of objects), but with no output schema, the description's enumeration of fields is sufficient for an agent to know what to expect.

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 zero parameters, so the schema provides no parameter documentation. The description compensates by explaining what the tool returns, which is the relevant semantic content. Since there are no parameters to document, the description fully covers the semantic space.

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 states a specific verb ('list') and resource ('video models'), and enumerates the exact attributes covered: lengths, resolutions, frame shapes, audio rendering, duration, and credit prices. This clearly distinguishes it from siblings like generate_video and get_credit_balance.

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

Usage Guidelines5/5

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

The description explicitly states when to use the tool: 'Use it to choose a model on price or capability, or to quote a cost before rendering.' This gives clear context and implies it should be used before generate_video, and it is not for checking balance (get_credit_balance) or retrieving a video (get_video).

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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