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Motion Control

create_motion_control

Make a character copy the motion of a reference video: the character in inputs.image performs the movement, dance or acting from inputs.video. Models: Kling 3.0 Pro / Standard, Kling 2.6 Pro, Wan 2.2 Animate, DreamActor v2 (see list_models). Priced live by the motion video's length — call get_price first. Poll with wait_for_video. Renders a live preview in app-capable hosts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoMode key from list_models. Omit to pick it from the attached media.
modelNoModel key from list_models (category "motion-control"). Default: kling-mc-3.0-pro.
inputsNoWaveSpeed input fields for the chosen model and mode, exactly as list_models shows them (e.g. aspect_ratio, resolution, duration, generate_audio, image, last_image, reference_images). Media fields take URLs; files hosted elsewhere are imported into the user's library automatically. Omitted fields use the model's defaults.
promptNoOptional guidance
maxCreditsNoRefuse to start if the live price is above this. Pass the credits get_price returned.
idempotencyKeyNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and delivers key traits beyond the schema: async execution requiring wait_for_video polling, live credit pricing tied to motion-video length, and live preview rendering in app-capable hosts. It omits auth requirements and failure/refund behavior, keeping it short of a 5.

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?

One tight paragraph, front-loaded with the core action, then models, pricing, polling, and preview in descending priority. Every sentence carries information an agent needs to invoke this correctly.

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 6-param async creation tool with no output schema, the description covers the essentials: what it produces, how to choose models, how it is priced, and how to await results. Only minor gaps remain (no output/return shape detail, no failure handling), but polling guidance compensates for the missing output schema.

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 83% (baseline 3), and the description adds genuine meaning by explaining the role split of the media inputs (image = performing character, video = motion reference) and pointing to list_models for mode/model keys and the WaveSpeed input fields. That extra role context lifts it above the schema baseline.

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?

States a specific verb and resource ('Make a character copy the motion of a reference video') and pins the exact input slots (inputs.image = character, inputs.video = motion source). This clearly distinguishes it from siblings like create_video and create_avatar_video without opening either schema.

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

Usage Guidelines4/5

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

Gives a clear operational sequence: check models via list_models, price via get_price first, then poll with wait_for_video. It stops short of an explicit when-not-to-use this over create_video/create_avatar_video, but the routing points to companion tools are strong and specific.

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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