Unity AI Bridge

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior by specifying what it bakes (Light Probe data and Lightmaps for static objects), prerequisites for lights, and post-bake verification steps. However, it does not mention potential side effects like performance impact, time requirements, or error handling, leaving some behavioral aspects unclear.

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 well-structured and concise, with three sentences that each serve a clear purpose: stating the tool's action, specifying prerequisites, and guiding post-bake verification. There is no redundant or unnecessary information, making it efficient and easy to understand.

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 (a baking operation with multiple parameters and no output schema), the description is mostly complete. It covers the purpose, usage guidelines, and behavioral context effectively. However, it lacks details on return values or error handling, which could be important for an agent invoking this tool, slightly reducing completeness.

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?

The input schema has 100% description coverage, so the baseline is 3. The description does not add any parameter-specific information beyond what the schema provides (e.g., it does not explain the implications of async vs. sync baking or the interaction between enableBakedGI and enableRealtimeGI). It relies entirely on the schema for parameter semantics.

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 tool's purpose with specific verbs ('Trigger light baking', 'Bakes Light Probe data') and resources ('in the current scene'), distinguishing it from siblings like 'lightprobe-analyze' (verification) and 'lightprobe-configure-lights' (setup). It explicitly mentions baking Light Probe data and Lightmaps for static objects, providing a precise scope.

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 explicit guidance on when to use this tool, including prerequisites ('Make sure lights are set to Baked or Mixed mode before baking') and references to sibling tools for setup ('use lightprobe-configure-lights') and verification ('Use lightprobe-analyze and console-get-logs to verify results after baking completes'). It clearly distinguishes this as the baking action tool versus configuration or analysis tools.

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