blend-ai

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set_rotation

Set an object's rotation in Blender using Euler angles in radians or quaternion WXYZ values, with Euler mode as the default.

Instructions

Set the rotation of an object.

Args: object_name: Name of the object. rotation: Rotation values. For EULER mode, XYZ angles in radians (3 elements). For QUATERNION mode, WXYZ values (4 elements). mode: Rotation mode, either EULER or QUATERNION. Defaults to EULER.

Returns: Dict with the object name and new rotation.

Input Schema

TableJSON Schema

Name	Required	Default
`mode`	No	EULER
`rotation`	Yes
`object_name`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed7 schema fields changedv1.7.0Sep 28, 2026
- addedInput schema / additionalProperties
```
Added value: +false
```
- addedInput schema / properties / mode / enum
```
Added value: +[
+  "EULER",
+  "QUATERNION"
+]
```
- 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 / rotation / maxItems
```
Added value: +3
```
- addedInput schema / properties / rotation / minItems
```
Added value: +3
```
- changedInput schema / required
```
Previous value: -[
-  "name",
-  "rotation"
-]New value: +[
+  "object_name",
+  "rotation"
+]
```
First observedv0.1.0Mar 22, 2026

TDQS

B3.3/5.0

Behavior3/5

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

No annotations exist, so the description carries the full burden. It does add useful behavior: the mode-dependent input format, the default mode, and that the return is a dict with the object name and new rotation. But it says nothing about overwriting existing rotation, required object state, or failure modes for a mutation tool.

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?

Front-loaded purpose followed by compact Args and Returns sections with no filler. The Args block is slightly verbose for three parameters but every line carries information.

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?

The core parameter semantics are covered and an output schema exists, so the Returns section is mildly redundant. However, for a mutation tool with zero annotation coverage, the absence of preconditions, state requirements, and the rotation-length conflict with the schema leaves real gaps.

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 largely does: object_name, the mode-dependent format of rotation (XYZ radians for EULER, WXYZ for QUATERNION), and the EULER default are all explained. One gap is that it asserts QUATERNION takes 4 elements while the schema pins rotation to exactly 3 items, leaving the agent with conflicting guidance.

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 and resource ('Set the rotation of an object'), which is unambiguous and clearly distinct from set_location/set_scale/set_pose in the sibling list. It stops short of explicitly naming those siblings or stating how it differs from apply_transforms, so differentiation is left to inference.

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 when-to-use guidance, no prerequisites (e.g., object must exist, be in object mode, or be selected), and no alternatives offered. The agent must infer all usage context.

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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