generate_image

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

The description adds significant value beyond annotations (openWorldHint, destructiveHint) by explaining the synchronous behavior, that it returns public URLs (and to pass them onward), and mentions the models used. No contradictions.

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 four sentences with no wasted words. It is front-loaded with the core purpose and models, then covers return format, synchronicity, and model details. Every sentence earns its place.

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 3 parameters, no output schema, and no nested objects, the description is complete. It explains the return format (public URLs), synchronicity, model choices, and how to handle the output. No gaps.

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?

With 100% schema coverage, the description still adds meaning: for 'prompt' it advises specificity on subject/style/composition/lighting; for 'model' it adds context on when to use each variant. The 'n' parameter does not get extra description, but overall adds value.

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 'Generate one or more images from a text prompt' providing a specific verb and resource. It distinguishes from sibling tools like generate_video by explicitly mentioning images and the model names.

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 gives contextual usage guidance by describing the two models with their trade-offs (quality vs. speed) and the synchronous nature. It implicitly differentiates from siblings, but does not explicitly state when not to use this tool.

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