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prompt-to-scene

prompt-to-scene

by 316sandon12
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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create_prop

Generate art-directed props with saved project style and automatic PBR baking for prompt-to-scene, then place or revise them in the active Blender-to-Unity scene.

Instructions

Create an art-directed prop using the saved project style and automatic PBR baking.

inspect_library lists nine recipes, parameters, parts and quality settings. Omit quality to inherit the project. New assets are placed near the camera; revisions keep transforms.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "kind": "<kind>",
      "asset_id": "<asset_id>"
    },
    "name": "create_prop"
  }
}

Input Schema

NameRequiredDescriptionDefault
kindYes
qualityNo
asset_idYes
colliderNo
positionNo
parametersNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.6.0

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations the description carries the full burden. It usefully discloses that PBR baking is automatic, that new assets are placed near the camera, and that revisions preserve transforms. It omits whether the call is long-running/async (siblings get_task_status/cancel_task imply tasks), what side effects occur, and any auth or permission requirements.

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?

Purpose is front-loaded in the first sentence, and the remaining sentences are short and information-dense with no filler. Slightly dense/fragmented but appropriately sized for the tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

A mutation/creation tool with no annotations, no output schema, and 0% parameter documentation should explain more. Key operational facts (async task behavior, return shape, what asset_id references, allowed kind values) are absent, leaving the agent under-informed for correct invocation.

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?

Schema description coverage is 0% across 6 parameters, so the description must compensate. It only clarifies the quality parameter ("omit quality to inherit the project"); the meaning of kind, asset_id, collider, position, and the free-form parameters object is left entirely undocumented.

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?

States a specific verb+resource ("Create an art-directed prop") plus the enabling mechanisms (saved project style, automatic PBR baking). It is clear what the tool does, though it never explicitly contrasts itself with the adjacent revise_prop/create_prop_set siblings.

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?

It implies a workflow (consult inspect_library for the nine recipes, parameters, parts and quality settings) and gives one concrete usage rule ("omit quality to inherit the project"). However there is no explicit when-to-use-this-vs-revise_prop guidance and no stated prerequisites.

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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