maya_worldlabs

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

Without annotations, the description takes full burden and discloses key behaviors: credit spending only with confirm=true, resumability via sidecar, that build runs in Maya, and draw_mode options. It could be improved by mentioning whether operations are destructive or reversible, but overall it is transparent.

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 comprehensive but verbose, containing several paragraphs and very detailed parameter lists. It is front-loaded with the purpose, but the length could be trimmed without losing essential information, making it less efficient for quick parsing.

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?

For a dispatch tool with 7 actions and no annotations, the description is mostly complete for inputs but lacks details on outputs per action (e.g., poll returns). The presence of an output schema (not shown) may mitigate this, but the description does not reference it, leaving a gap for agents.

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 is generic (only action and params as any), providing 0% coverage. The description fully compensates by listing all parameters for each action with types, examples, and optional flags, adding essential meaning beyond the schema.

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: generating a World Labs Gaussian-splat environment from an image and loading it into Maya for Arnold. It distinguishes the tool from siblings by its specific pipeline of actions, and the name itself signals the domain.

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 a clear pipeline order (generate → poll → download → convert → build) and gives explicit guidance on credit spending and resuming interrupted runs via status. However, it does not compare directly to sibling tools or state when not to use it, though the specialized nature makes alternatives obvious.

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