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Blender Copilot MCP Server

by dwgx

unity_create_animator

Create a Unity AnimatorController from a JSON blueprint. Define layers, states, transitions, and conditions to build animation controllers.

Instructions

Generate an AnimatorController from a JSON blueprint.

Parameters:

  • project_path: Unity project path

  • animator_json: JSON defining layers/states/transitions. Format: {"layers": [{"name": "FaceTracking", "defaultState": "Idle", "states": [{"name": "Idle", "motion": null}, {"name": "Smile", "motion": "Assets/Anims/Smile.anim"}], "transitions": [{"from": "Idle", "to": "Smile", "conditions": [{"param": "SmileWeight", "mode": "Greater", "threshold": 0.5}]}] }]}

  • output_path: Where to save .controller asset

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
output_pathNoAssets/VRC/FX.controller
project_pathNo
animator_jsonNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It states it generates an asset but does not disclose side effects like file overwriting, permissions required, or behavior on invalid JSON. Minimal behavioral context.

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 relatively concise, starting with a clear purpose then listing parameters. The JSON example is verbose but informative. No wasted sentences, though could be slightly shorter.

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?

Given the tool's complexity (JSON input) and presence of an output schema, the description covers the basic generation task but lacks context on what an AnimatorController is, error handling, or how to determine if the JSON is valid. Adequate but not thorough.

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?

With 0% schema description coverage, the description adds significant value by listing parameters and providing a detailed JSON format example for animator_json. It explains the required structure beyond the schema's defaults.

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 it generates an AnimatorController from a JSON blueprint. It specifies the verb and resource, but does not explicitly differentiate from sibling tools like vrc_generate_animator, leaving some ambiguity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives, no prerequisites or exclusions mentioned. The description assumes user knows the context, which is insufficient for an AI agent.

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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