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set_light_properties

Configure USD light prim properties by inserting an inline Python LOP after a specified node path, using prim path and property pairs to adjust lighting attributes.

Instructions

Set properties on a USD light prim via an inline Python LOP.

Args: node_path: LOP node path to connect after. prim_path: USD light prim path. properties: Property name-value pairs to set.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
node_pathYes
prim_pathYes
propertiesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2.24.1
    • addedInput schema / additionalProperties
      Added value: +false
  2. First observedv0.1.0

TDQS

C2.9/5.0
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. It discloses the mechanism ('via an inline Python LOP') and that node_path connects after an existing LOP, but it does not describe side effects, whether the light prim must already exist, what happens to unspecified properties, or any permission requirements.

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 clear first sentence and a compact Args section. Every line adds relevant information, and there is no wasted text.

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?

Given that the tool has no annotations, no output schema, a nested properties object, and 0% schema description coverage, the description is incomplete. It documents required arguments but omits when-to-use guidance, side effects, modification semantics, and return behavior.

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?

With 0% schema description coverage, the description usefully explains all three parameters: node_path as the LOP node to connect after, prim_path as the USD light prim path, and properties as name-value pairs. However, for the nested properties object it does not specify allowed property names, value types, or formatting, leaving meaningful ambiguity.

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: setting properties on a USD light prim via an inline Python LOP. This distinguishes it from generic attribute setting tools like set_usd_attribute, though it does not explicitly name a sibling alternative.

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 only lists arguments; it gives no guidance on when to use this tool versus alternatives such as create_light, set_usd_attribute, or list_lights. No prerequisites or exclusions are provided.

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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