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blend-ai

by HoldMyBeer-gg
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Python
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apply_transforms

Freeze an object's current location, rotation, and scale to make them the new transform basis in Blender, with selective application options.

Instructions

Apply (freeze) transforms on an object, making current transforms the new basis.

Args: object_name: Name of the object. location: Apply location transform. Defaults to True. rotation: Apply rotation transform. Defaults to True. scale: Apply scale transform. Defaults to True.

Returns: Confirmation dict.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scaleNo
locationNo
rotationNo
object_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 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"
+}
    • changedInput schema / required
      Previous value: -[
-  "name"
-]New value: +[
+  "object_name"
+]
  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 explains that transforms are frozen and become the new basis, but it does not disclose irreversibility, required permissions, or how object data is affected beyond that implied effect. This is a mutation tool with significant safety/profile gaps.

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 structured with a clear opening sentence followed by Args and Returns sections. It is front-loaded and not bloated, though the repeated 'Apply ... transform' phrasing is slightly repetitive.

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?

An output schema exists, so the description need not explain return values. It covers the operation and all parameters adequately for invocation, but it lacks usage context and safety/irreversibility details that would make it complete for a transform-mutating tool.

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 document parameters. It lists all four parameters, explains each boolean toggle ('Apply location/rotation/scale transform'), and gives defaults, which meaningfully compensates for the empty schema descriptions.

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: 'Apply (freeze) transforms on an object.' It also explains the effect ('making current transforms the new basis'), which distinguishes it from setters like set_location or set_rotation. However, it does not explicitly name or contrast with any sibling tool, so the distinguishing is implicit rather than explicit.

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 description gives the operation and parameter defaults but no guidance on when to use this tool versus alternatives such as set_location, set_rotation, set_scale, or apply_modifier. There is no explicit context, prerequisite, or exclusion.

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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