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Nexscope Ecommerce Data MCP

Happy Horse 2 Video Generation

nexscope_happy_horse_2_video_generation

Generate a Happy Horse 2 video from 1 to 9 required reference images. The model is fixed by this API, so videoType must not be supplied in the request.

Input Schema

NameRequiredDescriptionDefault
isProNoWhether to use the model's professional generation mode when supported. Defaults to false.
promptYesVideo generation prompt describing motion, subject consistency, camera movement, and the ecommerce scene. Maximum 10000 characters.
imageListYesPublic reference image URLs. Provide 1 to 9 images.
videoTimeYesVideo duration in seconds. Supported values: 5, 10, 15.
resolutionYesOutput resolution. Supported values: 720p, 1080p.
aspectRatioNoTarget video aspect ratio supported by this model. Supported values: 9:16, 16:9.
promptOptimizerNoWhether Nexscope should optimize the video prompt before generation. Defaults to false.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations only declare readOnlyHint=false and openWorldHint=true, so the description carries real weight. It usefully discloses a non-obvious constraint (videoType must not be supplied) that would otherwise cause a request error, but says nothing about cost, generation latency, or that the result is likely asynchronous and retrieved via nexscope_media_task_result.

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 short sentences, both front-loaded with actionable content, and no filler. The capability statement precedes the constraint in the right order for an agent scanning the definition.

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?

For a 7-parameter generation tool with no output schema, the description never says what comes back (a job id? a URL?) or whether the call is synchronous. Given the presence of a media task result sibling, omitting any mention of result retrieval is a meaningful gap for an otherwise simple 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?

Schema coverage is 100%, so the baseline is 3, but the description adds value beyond the schema by prohibiting a parameter (videoType) that is absent from the schema and permitted by additionalProperties=true — a genuinely useful guard. It restates the 1-9 image range, which is already in the schema, so it is not a 5.

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?

States a specific verb and resource ('Generate a Happy Horse 2 video') and names the input requirement (1-9 reference images). It identifies the model-specific scope, which is the main axis distinguishing it from the many other video-generation siblings, though it doesn't explicitly say how it differs from kling/seedance/wan alternatives.

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?

Usage is only implied by the model name — an agent must infer 'use this when the user wants Happy Horse 2 output' rather than the cheaper/faster alternatives. The videoType prohibition is a request constraint, not guidance on when to pick this tool, and no exclusions or comparisons are offered.

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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