text_to_image

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

Without annotations, the description must disclose behaviors. It mentions returning a task id, status, and output URLs but does not clarify that the tool is asynchronous (uses polling via `wait` parameter) or that it incurs costs. Key behavioral aspects are omitted.

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 (one sentence, 15 words), but it lacks structure and fails to provide essential details. It could be more informative without being verbose.

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 complexity (7 parameters, async behavior, no output schema), the description is grossly incomplete. It does not explain how to use the tool effectively, such as the required `quality` and `aspect_ratio` or the polling mechanism.

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 description adds no parameter-level semantics despite low schema coverage (29%). Parameters like `prompt`, `quality`, `aspect_ratio`, and polling-related fields are not explained. The description repeats only the basic output structure.

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: 'Create a GPT Image task on RunAPI (text to image).' This distinguishes it from sibling tools like edit_image and get_task, as it focuses on text-to-image generation.

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 (e.g., edit_image). No context on prerequisites, use cases, or exclusions is given.

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