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blend-ai

by HoldMyBeer-gg
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Python
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set_light_property

Adjust light properties such as energy, color, and shadow softness on Blender light objects to control scene illumination.

Instructions

Set a property on a light object.

Args: object_name: Name of the light object. property: Property to set. One of: energy, color, shadow_soft_size, spot_size, spot_blend, area_size, area_size_y, use_shadow, angle, specular_factor, diffuse_factor, volume_factor. value: The value to set. Type depends on the property.

Returns: Confirmation dict.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
valueYes
propertyYes
object_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changedv1.7.0
    • addedInput schema / additionalProperties
      Added value: +false
    • 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 / property / enum
      Added value: +[
+  "angle",
+  "area_size",
+  "area_size_y",
+  "color",
+  "diffuse_factor",
+  "energy",
+  "shadow_soft_size",
+  "specular_factor",
+  "spot_blend",
+  "spot_size",
+  "use_shadow",
+  "volume_factor"
+]
    • changedInput schema / required
      Previous value: -[
-  "name",
-  "property",
-  "value"
-]New value: +[
+  "object_name",
+  "property",
+  "value"
+]
  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 burden of behavioral disclosure. It states only 'Set a property' and 'Returns: Confirmation dict,' without describing side effects, required object state, permissions, reversibility, or possible errors. For a mutation tool with zero annotations, this is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with a one-sentence purpose, then organized into Args and Returns sections. The property list is necessary and no sentences are wasted. It is appropriately sized for a three-parameter tool.

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?

Although an output schema exists and reduces the need to explain return values, the tool has no annotations and 0% schema description coverage. The description covers parameter names and property values but omits value-type details and behavioral side effects. It is minimally sufficient for invocation but not fully complete for safe use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

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. It names all three parameters, lists the allowed property values, and notes that value type depends on the property. However, it does not specify the expected value type per property or clarify object_name constraints, so it only partially compensates for the missing 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: 'Set a property on a light object.' It clearly identifies the operation and target object type. However, it does not distinguish this tool from siblings such as set_shadow_settings, set_material_property, or set_object_visibility, 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?

The description provides no when-to-use guidance, no prerequisites, and no alternatives. It does not explain when an agent should choose set_light_property over related tools like set_shadow_settings or create_light. It only lists arguments and return format, leaving usage context entirely implicit.

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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