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create_light

Create a light in Blender by specifying type, location, color, energy, and shadow parameters for point, sun, area, or spot lights.

Instructions

Create a light.

For a quick, even setup to inspect an asset, use create_preview_lighting instead of placing lights one at a time.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
sizeNoAREA light size; bigger means softer shadows
typeNoLight typePOINT
angleNoSUN angular diameter in degrees; larger softens shadows
colorNo[r, g, b] or [r, g, b, a], each 0..1 (linear)
energyNoWatts for POINT/SPOT/AREA (100-1000 is typical a few metres away); irradiance for SUN (1-5 is daylight)
look_atNo[x, y, z] in Blender units
locationNo[x, y, z] in Blender units
rotationNo[x, y, z] in DEGREES. Only matters for SUN, SPOT and AREA.
spot_sizeNoSPOT cone angle in degrees
collectionNo
spot_blendNo
look_at_objectNo
shadow_soft_sizeNoPOINT/SPOT radius; bigger means softer shadows

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.7/5.0
Behavior2/5

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

Annotations are absent, so the description carries the full burden of behavioral disclosure. It only repeats the creation intent without mentioning side effects, prerequisites, return behavior, or interactions with the scene. For a mutation tool, this is a notable 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 extremely concise, using only two sentences. The core purpose is front-loaded in the first sentence, and the alternative guidance is clearly separated. Every word earns its place.

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

Completeness2/5

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

With 14 parameters星的, no output schema, and no annotations, this tool is complex, yet the description provides almost no contextual overlay. It does not explain typical use cases (e.g., which parameters matter for which light type), what the tool returns, or what conditions must be met. The schema gives some per-parameter meaning, but the overall call context is under-specified.

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

Parameters2/5

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

The description adds no parameter-level meaning; it only says 'Create a light.' The input schema covers 10 of 14 parameters with descriptions (71% coverage), leaving 4 parameters (name, collection, spot_blend, look_at_object) undocumented in both schema and description. The description fails to compensate for the missing 29%.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear verb and resource: 'Create a light.' It also explicitly names the sibling tool create_preview_lighting as an alternative for a different use case, which distinguishes it from that sibling and makes its purpose unambiguous.

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

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says when not to use this tool: 'For a quick, even setup to inspect an asset, use create_preview_lighting instead of placing lights one at a time.' This names the alternative and provides a specific condition, giving the agent a clear when-to/when-not-to decision.

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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