gpt_image_generate

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

No annotations are provided, so the description must disclose behavior. It reveals that the tool automatically waits for completion and returns imagePaths, and on timeout returns a taskId for later retrieval. This is decent disclosure, but it omits information about authorization requirements, rate limits, or potential side effects (though the tool is not destructive).

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 a single paragraph that front-loads the main purpose and then lists key parameters. It is concise with no redundant information. However, it could be slightly more structured (e.g., using bullet points) for easier scanning.

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 (12 parameters, one required), the description covers the essential operations and return behavior, including timeout handling. The output schema exists, so return values need not be detailed. However, several parameters (size, n, output_compression) are left unexplained, which may cause confusion for an AI agent.

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 0%, so the description should compensate. It explains operation, images (with format), input_fidelity, quality, background, output_format, and timeout behavior. However, it does not explain n, size, model_name, timeout_seconds, or output_compression. The partial coverage is helpful but insufficient for all 12 parameters.

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 performs GPT image generation (gpt-image-2) with two modes: generate (text-to-image) and edit (image-to-image). It also mentions returning imagePaths and timeout behavior, differentiating from the sibling gpt_image_result. However, it does not explicitly distinguish from other generation tools like doubao_image_pro_generate.

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 usage context for the 'edit' operation (images required, format, input_fidelity) and timeout fallback (use gpt_image_result). It does not compare with other image generation tools or specify when to avoid this tool. Usage is implied rather than explicit.

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