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jonit-dev
by jonit-dev

Retarget selected donor clips onto a prepared target

asset_retarget_animations
Idempotent

Fetch the selected pinned release donors, retarget their clips onto a prepared target skeleton with a world-space rest correction, preserve the target's mesh/materials/UVs and (by default) its existing clips, and publish a game minimal…

Instructions

Fetch the selected pinned release donors, retarget their clips onto a prepared target skeleton with a world-space rest correction, preserve the target's mesh/materials/UVs and (by default) its existing clips, and publish a game minimal GLB. Root motion requires the matching _RM donor.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
clipsYes
outputYesOutput .glb path under projectRoot.
targetYesAbsolute path to the prepared target GLB (e.g. the AETHER sample).
mappingNo
priorDigestNo
projectRootYesProject root that must contain the output.
keepExistingClipsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
bytesYes
clipsYes
outputYes
sha256Yes
statusYes
mappingYes
replacedYes
alreadyExistedYes
animationBytesYes
animationCountYes
meshTextureBytesYes
keepExistingClipsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.1

TDQS

A4.4/5.0
Behavior4/5

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

The description discloses meaningful behavior beyond the annotations: it preserves the target's mesh/materials/UVs and existing clips by default, applies a world-space rest correction, and publishes a minimal GLB. These details align with idempotentHint and destructiveHint=false; no contradiction 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?

Two tightly packed sentences front-load the main action and then add the most important behavioral caveat. There is no filler or repetition.

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 complex 7-parameter pipeline, the description captures the core workflow, key side effects, and the root-motion requirement. The main gap is no mention of mapping or priorDigest, but the output schema and annotations fill some surrounding context.

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 low at 43%, but the description compensates for key parameters: clips are 'pinned release donors', target is a 'prepared target skeleton', output is a 'game minimal GLB', keepExistingClips is 'by default its existing clips', and root_motion maps to the '_RM donor' rule. It leaves mapping and priorDigest unexplained, but the core workflow parameters are clarified.

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 states a specific multi-step action: fetch pinned release donors, retarget clips onto a prepared target skeleton, preserve target attributes, and publish a game minimal GLB. This clearly differentiates it from sibling search, download, and preview tools.

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 clear context: it is for retargeting pinned release donor clips onto an already prepared target, with a root-motion caveat about needing the matching _RM donor. It does not explicitly name alternatives or when-not-to-use conditions, but the scope is clear enough.

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