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Nexscope Ecommerce Data MCP

Kling 3 Omni Video Generation

nexscope_kling_3_omni_video_generation

Generate a Kling 3 Omni video using first/last frames or up to 7 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.
imageUrlNoPublic URL of a first-frame or primary reference image.
imageListNoPublic reference image URLs. Provide 1 to 7 images.
videoTimeYesVideo duration in seconds. Supported values: 5, 10, 15.
resolutionNoOutput resolution. Supported values: 720p, 1080p.
aspectRatioNoTarget video aspect ratio supported by this model. Supported values: 1:1, 9:16, 16:9.
promptOptimizerNoWhether Nexscope should optimize the video prompt before generation. Defaults to false.
lastFrameImageUrlNoOptional public URL of the final-frame image. Requires 1080p.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=false and openWorldHint=true, so the agent knows this is an outward-facing write/generation call. The description adds the useful constraint that the model is fixed and videoType must be omitted, but it says nothing about the likely asynchronous flow (the sibling nexscope_media_task_result implies a task id must be polled), expected generation latency, cost, or how reference images interact with first/last-frame modes.

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, front-loaded with the capability and followed by the one non-obvious request constraint. No filler, no restatement of the title.

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?

For a nine-parameter generative media tool with no output schema, the description should explain the operational contract — that this likely creates a task whose result is fetched elsewhere, how longFrameImageUrl and imageList modes interact, and prompt expectations. None of that is present, leaving the agent to infer the async workflow from sibling names.

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

Parameters3/5

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

Schema description coverage is 100%, so all nine parameters including enums and the lastFrameImageUrl 1080p requirement are already documented structurally. The description only reinforces that images can be first/last frames or up to seven references and that videoType must be excluded; it adds little new semantic detail. Baseline 3 applies when the schema does the heavy lifting.

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 Kling 3 Omni video") and names the input modes (first/last frames, up to 7 reference images), so the agent knows exactly what capability this is. It does not, however, differentiate itself from the many sibling video generators (nexscope_kling_2_6_video_generation, nexscope_seedance_2_5_video_generation, nexscope_wan_3_video_generation, nexscope_hailuo_2_3_video_generation, etc.) beyond the model name.

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?

There is no guidance on when to choose this model over the numerous sibling video-generation tools, nor any stated prerequisites or typical use case (e.g. ecommerce product b-roll). The only rule given is a negative constraint about not supplying videoType, which is a validity rule rather than usage guidance.

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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