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gen_uthana_video_to_motion

Convert a reference video into a motion asset by creating a Uthana video-to-motion job, with explicit approval required before processing.

Instructions

Create a Uthana video-to-motion job after explicit usage approval.

KB: see knowledge_base/31_GENERATIVE_CONTENT_PIPELINE.md#uthana-motion-task-family Example: gen_uthana_video_to_motion(video_file="C:/capture/reference.mp4", motion_name="A_ReferenceMove", confirm_usage=True)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNovideo-to-motion-v2
timeout_sNo
video_fileYes
motion_nameNo
character_idNo
session_nameNodefault
confirm_usageNo
estimated_secondsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It mentions usage approval but does not describe side effects, job lifecycle, whether it blocks, or cost implications. The timeout parameter exists in the schema but is not explained in the description, leaving the agent guessing about execution behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief and to the point, with a useful example and KB pointer. It front-loads the purpose and does not waste words, though it could be slightly more structured to enumerate parameter semantics.

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?

The tool has 8 parameters, no annotations, no parameter descriptions in the schema, and the description only partially covers them. While an output schema exists (which spares explanation of return values), the lack of parameter documentation and behavioral detail makes the definition incomplete for an agent to call it reliably.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must explain all parameters. It only mentions video_file, motion_name, and confirm_usage in the example, leaving model, timeout_s, character_id, session_name, and estimated_seconds undefined. The example gives some meaning to the core parameters but is far from complete for an 8-parameter tool.

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?

The description clearly states the verb 'Create' and the resource 'Uthana video-to-motion job', which is specific and distinguishes it from text-to-motion or other generative tools. It also mentions usage approval, but does not clarify what the job produces or returns, so it stops short of a 5.

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?

The phrase 'after explicit usage approval' hints at a high-cost operation, and the KB reference provides context, but there is no explicit guidance on when to use this tool versus alternatives like gen_uthana_text_to_motion. The example demonstrates invocation but not selection criteria.

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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