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kaziislam11
by kaziislam11

motion studio save animation

motion_studio_save_animation

Save a library animation as a native KeyframeSequence in the rig's AnimSaves location, recording undo and referencing a ServerStorage folder without uploading or publishing.

Instructions

Save a library animation as a new native KeyframeSequence in the rig's AnimSaves location, with an undo recording. New saves use a ServerStorage folder referenced by an ObjectValue. Does not upload or publish.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rigIdYesStable selected model ID from motion_studio_sessions.
assetIdYes
jointMapNoOptional recipe joint name to actual rig part/bone name mapping. Does not convert local axes.
sessionIdNoStudio session from motion_studio_sessions. Required when multiple sessions are connected.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

The description discloses that it creates a new KeyframeSequence, records undo, and uses a ServerStorage folder for storage. Since annotations provide no hints (all false), the description carries the full burden and covers the main side effects without hiding mutation behavior.

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 concise at two sentences, uses precise technical terms, and avoids unnecessary elaboration. It is well-structured and immediately conveys the core functionality.

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?

The description sufficiently explains the core purpose and storage behavior, but it does not mention expected inputs or output. The ambiguity around assetId and the lack of any information about return values means an agent may struggle to fully use the tool without additional context.

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?

The description does not explain any parameters. The schema provides descriptions for rigId, jointMap, and sessionId, but assetId's description is only a $ref to sessionId's description, leaving a required parameter ambiguous. The tool description offers no clarification on what assetId represents.

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 ('Save a library animation'), the specific output ('new native KeyframeSequence'), the location ('rig's AnimSaves location'), and includes an explicit non-goal ('Does not upload or publish'). It distinguishes this tool from siblings like motion_studio_save_vfx or motion_library_save.

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 implies when to use this tool by specifying it saves to a local rig location and explicitly excludes upload/publish behavior. It does not directly compare with alternatives like motion_library_save, but the behavioral details provide sufficient context for an agent to infer the appropriate use case.

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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