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

Annotations only declare openWorldHint, so the description carries most of the burden — and it delivers the key behavioral trait: the call is asynchronous and returns a request ID rather than an image, retrieved later via fetch-image. It does not cover auth, rate limits, or what happens if the request fails, keeping it below a 5.

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?

Three short sentences with the core action front-loaded and the async retrieval flow second. The closing sentence ('Supports various AI image generation models') is mild filler since model_id already implies this, so it is not maximally tight.

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?

With no output schema, the description usefully compensates by explaining that the return value is a request ID consumed by fetch-image. Combined with 100% schema coverage and the openWorldHint annotation, an agent has enough to call it correctly; the webhook and failure behavior remain unaddressed.

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 100%, so every parameter (width, height, samples, webhook, negative_prompt, aspect_ratio, track_id, model_id) is already documented with examples and ranges. The description adds no format, default, or interaction detail beyond the schema, so the baseline of 3 applies.

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?

States a specific verb and resource ('Generate images from text prompts') and names the mechanism ('using AI models'). This cleanly separates it from siblings like image-to-image, text-to-video, and inpaint-image, which take different inputs.

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 routes the agent downstream by naming fetch-image as the retrieval tool and explaining the request-ID handoff, which is genuine usage guidance for an async tool. It stops short of stating when to prefer this over alternatives such as image-to-image or a specific model family, so it lacks explicit exclusions.

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