generate_image

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the return format but omits critical details like rate limits, authentication requirements, error handling, or processing time. For a generative tool with potential costs or delays, this is a significant gap in transparency.

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 well-structured with clear sections (Args, Returns) and front-loaded the core purpose. It avoids redundancy, though the 'Returns' section could be omitted since an output schema exists, slightly reducing efficiency.

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 (5 parameters, generative function) and no annotations, the description is moderately complete. It covers parameters and output format (aided by the output schema) but lacks behavioral context like costs, limitations, or integration details, leaving gaps for effective agent use.

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 substantial value beyond the input schema, which has 0% description coverage. It explains each parameter's purpose (e.g., 'model' specifies which AI model to use) and lists valid options for 'model', 'size', 'quality', and 'style', compensating well for the schema's lack of documentation.

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 specific action ('Generate a single image') and resource ('from a text prompt'), distinguishing it from sibling tools like 'start_image_batch' (batch processing) or 'get_next_image' (retrieval). It precisely communicates the tool's function without ambiguity.

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 like 'start_image_batch' for multiple images or 'list_models' for model information. It lacks context about prerequisites, constraints, or typical use cases, offering only basic operational information.

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