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

Annotations include openWorldHint=true, so the description should disclose side effects. It adds context about the AI art-director refinement and inline rendering, but does not mention potential costs, duration, or output behavior beyond the viewer. The description partially compensates for missing annotation details.

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 extremely concise (two sentences, 55 words) and front-loads the core purpose. Every sentence adds value, with no redundancy or filler.

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 tool with two optional parameters and no output schema, the description explains the main workflow (text or image) and a key behavioral aspect (art-direction). However, it omits details about what happens when both inputs are provided and does not clarify the return format or how the inline viewer is presented.

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?

Input schema covers 100% of parameters with descriptions. The description reinforces that prompt is for a single subject and that image_url is optional, but adds little new meaning beyond the schema. The art-director refinement is mentioned but not tied to a specific parameter.

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 that the tool generates a textured 3D mesh (GLB) from a text prompt or reference image URL. It includes an art-direction step for text prompts, which distinguishes it from simpler generation tools. However, it does not explicitly differentiate from siblings like forge_free or text_to_avatar, which may overlap.

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 its siblings (e.g., forge_avatar, forge_free) or alternatives. It implies a single-subject focus but does not state exclusions or when not to use it.

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