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Cartwhl
by Cartwhl

generate_motion

Transform text descriptions into animated 3D character motions with configurable export format, frame rate, and model. Get a batch ID for progress tracking.

Instructions

Generates motion animation based on text prompts. Returns a batch ID for tracking the generation progress. Consumes generation credits. Submit once, then use get_batch and list_batch_motions to poll; do not resubmit to check progress.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
loopNoIf true, the motion generation will be looped on a seamless repeat. Applied to all motions in a batch. Defaults to false.
promptsYesThe prompts describing the desired motions
batchNameNoAn optional name to be associated with the batch. Will be used to identify the batch in the Cartwheel UI and email notifications.
exportSettingsYesThe export settings for the motion generation
requestedModelYesThe model to use for the motion generation
swingPropertiesNoOptional parameters specific to the 'swing' model. Ignored if requestedModel is not 'swing'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the annotations, the description discloses that the call consumes generation credits, returns a batch ID for tracking, and should not be repeated merely to check progress. This is important side-effect and lifecycle information that the annotations alone do not provide. No contradiction with the annotations exists.

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 three short, purposeful sentences: it states the action, the return value, and the critical usage caveat about credits and polling. Every sentence adds value and there is no redundancy or filler.

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

Completeness5/5

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

For an asynchronous creation tool with no output schema, the description provides the essential return contract (a batch ID), the cost implication (credits), and the follow-up polling tools. Together with the fully documented input schema, an agent has enough context to invoke the tool correctly and avoid common misuse.

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%, and every parameter including nested objects has detailed descriptions, examples, enums, and defaults. The description itself adds no parameter-specific semantics, but the schema fully carries that burden, so the baseline score of 3 is appropriate.

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 clearly states the action and resource: 'Generates motion animation based on text prompts.' It also distinguishes itself from the sibling generate_motion_from_video by specifying the text-prompt input modality, and clarifies it is a creation/submission tool rather than a retrieval or listing tool.

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?

The description gives explicit workflow guidance: submit once, then use get_batch and list_batch_motions to poll, and do not resubmit to check progress. It does not explicitly name generate_motion_from_video as the video alternative, but the text-prompt qualifier and sibling names make the choice reasonably clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.