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prompt-to-scene

prompt-to-scene

by 316sandon12
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Python
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inspect_scene

Read the active scene and selected managed props to resolve 'this object' references. Use it to identify current selections for accurate Blender Python authoring or Unity placement.

Instructions

Read the active scene and actual selected managed props to resolve 'this object'.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "inspect_scene"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.6.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. 'Read' implies a safe, non-mutating operation, and 'actual selected' usefully signals it reflects live state rather than a declared selection. Beyond that, no return format, side effects, or permission requirements are disclosed.

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?

A single front-loaded sentence with no padding, and the core action leads. It is slightly cryptic in places ('managed props', 'this object') but every word carries weight.

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?

For a zero-parameter read tool with no output schema, the agent still cannot tell what a 'scene' read returns or what 'managed props' are. Complexity is low, so this is adequate but not complete.

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?

The tool takes zero parameters, so there is nothing for the description to document; baseline 4 applies. No parameter-related misinformation is present.

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 ('read') and resource ('active scene and actual selected managed props'), and adds the goal of resolving 'this object'. However, it doesn't distinguish itself from nearby siblings like inspect_target, inspect_asset, or inspect_library, leaving the agent to infer the difference.

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?

The phrase 'to resolve this object' hints at a scenario, but there is no explicit when-to-use, no exclusions, and no named alternative such as inspect_target. The agent gets a rationale rather than routing guidance.

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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