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Retarget Animation Clip

retarget_animation
Read-onlyIdempotent

Retarget a built-in animation clip to a platform mapping and report coverage + deterministic hashes. [Paid: $0.75 USDC via x402 for unauthenticated calls on the hosted /mcp endpoint; settled only on a successful (non-error) result.]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
platformYesTarget platform mapping
clip_nameYesBuilt-in clip name from animation library
drop_unmappedNoDrop channels not found in the target mapping

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds valuable context beyond annotations: the paid cost ($0.75 USDC via x402), the fact that it only works with built-in clips, and the note that it reports coverage and deterministic hashes. This enriches the agent's understanding of the tool's behavior without contradicting the hints.

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 two sentences: the first states the purpose and outcome, the second discloses the cost and payment model. Both sentences earn their place, with no redundancy or filler. It is concise, front-loaded with the primary action, and structured for quick comprehension.

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?

Given the tool's moderate complexity (3 params, 2 required), the description covers the core functionality, cost, and a key constraint (built-in clips). It also indicates the output type (coverage + hashes) even though no output schema exists. Missing are explicit details on error behavior or output structure, but the description is adequate for an agent to select and invoke the tool correctly.

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?

The input schema provides 100% description coverage for all parameters (platform, clip_name, drop_unmapped), so the baseline for this dimension is 3. The description adds no extra parameter-level detail beyond what the schema already conveys, though it does mention 'built-in' which aligns with clip_name's schema description.

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 uses a specific verb ('retarget') and resource ('built-in animation clip') and clearly states the outcome ('report coverage + deterministic hashes'). It distinguishes from sibling tools like axis_compare or generate_avatar_from_image by focusing exclusively on animation retargeting across platform mappings.

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?

Usage context is implied: the tool is for retargeting built-in animation clips to a specific platform mapping. However, it does not explicitly contrast with alternatives or state when not to use it, so it lacks the explicit when/when-not guidance that would merit a 4 or 5.

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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TDQS

A4/5.0
Disambiguation5/5

Each tool occupies a clearly distinct role: generation (image/text) plus status polling, pipeline processing (file vs inline), validation, repair, export, compliance, manifest verification, inspection, comparison, capabilities, and animation retargeting are all separated. The only potential overlap between axis_process and post_process_mesh is explicitly resolved by input method and scope.

Naming Consistency3/5

Two naming styles coexist: axis_* prefix for core pipeline/contract tools and descriptive non-prefixed names for generation, repair, and compliance tools. Within axis_*, the verb/noun order is inconsistent (e.g., axis_manifest_verify vs axis_list_capabilities), making the set readable but not uniform.

Tool Count5/5

14 tools is squarely within the ideal 3-15 range and matches the broad but well-defined scope of a full avatar foundry: generation, processing, validation, repair, export, compliance, and metadata inspection. Every tool serves a necessary function with no redundancy or bloat.

Completeness4/5

The toolset covers the full lifecycle from generation (image/text) and status polling through post-processing, repair, validation, export, and Roblox-specific compliance. Minor gaps exist, such as no tool to list available animation clips (retarget_animation references 'built-in' clips) or manage a library of previously generated avatars, but core workflows are fully supported.

Resources