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 adds valuable context by specifying the default model (gemini-3.1-flash-image-preview), batch generation capability, and the response format (thumbnail preview) plus the full-resolution save location (/root/nano-banana-output). This goes beyond the basic function and discloses the side effect of saving a file to disk.

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 three sentences long, each earning its place: the first states the core purpose, the second gives the default model and batch support, and the third explains output behavior. It is front-loaded with the most important information and contains no filler or repetition.

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 there is no output schema, the description adequately covers return values by stating that a thumbnail preview is returned and the full-resolution image is saved to a specific path. It also provides the default model and batch range. It could be more complete by mentioning potential errors or limitations, but for a generation tool this is a solid level of context.

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 schema already provides detailed descriptions for all 6 parameters (100% coverage), so the description does not need to explain parameter syntax. It does touch on batch generation (n=1-4), which aligns with the schema, but adds no semantic nuance beyond what the schema already offers. The baseline of 3 is appropriate since the schema handles the heavy lifting.

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 function with a specific verb and resource: 'Generate an image from a text prompt using Google Gemini.' This not only describes what it does but also naturally distinguishes it from its siblings (edit_image, describe_image), as those involve modifying or analyzing images rather than creating them.

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 implies the tool is for generating new images from prompts, which provides clear context for when to use it. However, it does not explicitly mention alternatives or exclusions, such as 'for editing existing images use edit_image' or 'use describe_image to analyze an image.' The usage guidance is therefore implied rather than explicitly stated.

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