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Blender Copilot MCP Server

by dwgx

vrc_setup_visemes

Set up VRChat viseme shape keys for lip sync on a mesh. Supports template creation, renaming, MMD vowel mapping, or generating from base mouth shapes.

Instructions

Set up VRChat viseme shape keys (lip sync) on a mesh.

Parameters:

  • mesh_name: Target mesh. If empty, uses mesh named "Body" or the first mesh found.

  • mode: "template" creates empty viseme shape keys as placeholders. "rename" renames existing shape keys using source_mapping. "from_mmd" auto-maps MMD vowel shapes (あいうえお) to VRC visemes. "from_base_shapes" generates all 15 visemes by blending 3 base mouth shapes (CATS technique). Requires source_mapping with keys: mouth_a, mouth_o, mouth_ch. Example: '{"mouth_a": "あ", "mouth_o": "お", "mouth_ch": "い"}'

  • source_mapping: JSON mapping. Usage depends on mode.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNotemplate
mesh_nameNo
source_mappingNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It explains that shape keys are created, renamed, mapped, or blended depending on mode, but does not disclose potential side effects like overwriting existing shape keys or prerequisites (e.g., mesh must have certain base shapes). The behavior is partially transparent but could be more explicit about risks.

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 well-structured with a clear opening sentence followed by parameter explanations in a bullet-like format using dashes. It is informative but not overly verbose. Minor improvements could include grouping mode descriptions more compactly.

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 presence of an output schema (context indicates it exists), the description does not need to explain return values. The tool has 3 parameters (0 required) and the description covers their semantics and defaults. It feels complete for the use case, though error handling or validation notes are absent.

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 description coverage is 0%, yet the description effectively explains all three parameters: mesh_name (defaults, target mesh), mode (four values with specific behaviors), and source_mapping (JSON mapping, usage depends on mode). This adds significant value beyond the minimal schema, though examples for source_mapping could be clearer.

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 explicitly states the tool's purpose: setting up VRChat viseme shape keys for lip sync on a mesh. It clearly distinguishes from sibling tools (e.g., vrc_setup_eye_tracking, vrc_setup_gestures) which have different functions.

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 details four modes (template, rename, from_mmd, from_base_shapes) with concise explanations of each. While it doesn't explicitly state when to use each or mention alternatives, the mode descriptions imply the appropriate use cases. Some guidance on when not to use certain modes would improve clarity.

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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