set_light_properties

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 the tool 'sets properties' but doesn't disclose whether this is a mutating operation, whether it requires a specific LOP context, whether it cooks the node, or what happens if the prim doesn't exist. The mention of 'inline Python LOP' hints at implementation but doesn't explain side effects or prerequisites.

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

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

The description is concise and front-loaded with the main purpose. The Args section is a compact list that maps directly to the parameters. It's efficient with no wasted words, though the parameter explanations are terse to the point of being under-specified.

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

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

Given the tool's complexity (3 required params, nested object, no output schema, no annotations), the description is incomplete. It doesn't explain the expected structure of the 'properties' object, whether the LOP node is created or must exist, what 'connect after' means in the node graph, or what the tool returns. An agent would need to guess or inspect other tools to use this correctly.

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

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 lists the three parameters (node_path, prim_path, properties) with brief explanations, but these are minimal and don't add meaning beyond the parameter names. For example, it doesn't explain what 'connect after' means, what format properties should take, or how the LOP node is created/used. The description adds some value by naming the parameters, but not enough to fully compensate for the lack of schema descriptions.

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

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

The description clearly states the action: 'Set properties on a USD light prim via an inline Python LOP.' It identifies the resource (USD light prim) and the mechanism (inline Python LOP). It doesn't explicitly distinguish from sibling tools like set_usd_attribute or set_parameter, but the specific mention of 'light prim' and 'properties' provides enough clarity for an agent to understand the tool's purpose.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention that this is for USD light prims specifically, nor does it contrast with set_usd_attribute, set_parameter, or create_light. The agent is left to infer usage from the name and description alone, with no exclusions or alternative routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.