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cristoferarango

blender-studio-pro-mcp

set_light_property

Change any property of a Blender light's data block by providing the light name, property key, and new value.

Instructions

Set a property on a light's data block.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
valueYes
propertyYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior1/5

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

No annotations are provided, and the description offers no behavioral details. It does not disclose side effects, error conditions, return values, or requirements like the existence of the light. For a mutating operation with zero annotation coverage, the description fails to convey any behavioral transparency beyond the fact that it sets a property.

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

Conciseness3/5

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

The description is extremely concise, with a single sentence that states the core action. It is front-loaded and free of fluff, but it is under-specified. The brevity does not serve the agent because critical information about parameters and usage is omitted. It is not wasteful, but it sacrifices completeness for conciseness, earning a mid-range score.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 0% schema coverage, no annotations, and a mutation tool with three required parameters, the description is grossly incomplete. It does not explain valid property names, how to specify the light, what values are acceptable, or what the output schema contains. An agent cannot reliably call this tool without additional context. The description provides almost no value toward correct invocation.

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

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, meaning the input schema has no descriptions for name, property, or value. The description does not compensate by explaining these parameters. It does not clarify what valid property names are, how the light is identified, or what value format is expected. With no additional context, the agent must infer all parameter semantics from the property names alone, which is insufficient.

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 clearly states the verb 'Set' and the resource 'a light's data block', indicating it modifies a light property. It is specific enough to distinguish from many other set_* tools, though it doesn't name the exact property types or the light identifier. It is a clear, single-purpose statement but lacks differentiation from other light-related setters like set_light_intensity (not present), which is mitigated by the general wording.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

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 description does not mention any conditions, prerequisites, or fallback tools. With many sibling tools like create_light, delete_light, and set_bone_property, the agent is left without context on when this specific setter is appropriate, making the description unhelpful for selection.

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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