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blend-ai

by HoldMyBeer-gg
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Python
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set_scale

Adjust an object's XYZ scale in Blender by passing its name and a three-number scale; returns the object name and updated scale.

Instructions

Set the scale of an object.

Args: object_name: Name of the object. scale: XYZ scale as a 3-element list/tuple.

Returns: Dict with the object name and new scale.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scaleYes
object_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changedv1.7.0
    • removedInput schema / properties / name
      Removed value: -{
-  "title": "Name",
-  "type": "string"
-}
    • addedInput schema / properties / object_name
      Added value: +{
+  "title": "Object Name",
+  "type": "string"
+}
    • addedInput schema / properties / scale / maxItems
      Added value: +3
    • addedInput schema / properties / scale / minItems
      Added value: +3
    • changedInput schema / required
      Previous value: -[
-  "name",
-  "scale"
-]New value: +[
+  "object_name",
+  "scale"
+]
  2. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It says the tool mutates an object's scale and returns a dict with the name and new scale, but it omits key side-effect details: whether the scale is local or global, whether it is absolute or relative, whether children are affected, and what permissions or prerequisites are needed.

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 short and front-loaded with the action, followed by clear Args and Returns sections. The Returns section repeats what the output schema already provides, which is slightly redundant, but overall the text is efficient and well structured.

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 no annotations, 0% schema description coverage, and an output schema that already covers return values, the description should carry more behavioral context. It tells the agent how to call the tool and what it returns, but key operational details such as coordinate space, units, and transform side effects are missing.

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%, so the description must compensate, and it does document both parameters. It adds 'XYZ' and '3-element list/tuple' meaning to the scale array, which goes beyond the schema's type and min/max constraints. The object_name explanation is trivial but still present, so this is solidly above baseline for low coverage.

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 states a specific verb and resource: 'Set the scale of an object.' It is immediately clear what the tool does. It does not differentiate itself from nearby transform siblings such as set_location, set_rotation, or apply_transforms, so it falls short of a 5.

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?

There is no guidance on when to use this tool versus alternatives. The transform siblings (set_location, set_rotation, apply_transforms) are not mentioned, and no prerequisites or conditions are provided. The agent must infer usage entirely from the name.

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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