generate_image

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

Discloses behavioral traits: supported models, constraints per model (e.g., max reference images, supported resolutions/aspect ratios), file types, output location, and base64 return. Lacks info on auth, rate limits, but is sufficient.

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?

Information is well-structured and front-loaded. Slightly long but every sentence adds value. Could be trimmed slightly without loss of clarity.

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?

For a complex tool with 8 parameters and no output schema, description covers model differences, constraints, output location, and return format. Lacks error handling details but is complete enough.

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 coverage is 100%, and description adds extra context (e.g., model tiers, limitations, supported file types) that goes beyond schema descriptions, enriching parameter meaning.

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?

Clearly states 'Generate images using Gemini's native image generation' and lists specific models. Distinguishes from sibling tools like generate_speech and generate_video by focusing on 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?

Provides detailed guidance on which model to use for specific needs (e.g., fast/low-cost tier, required model for certain resolutions/aspect ratios). However, does not explicitly compare against sibling tools like generate_video, but context makes it clear.

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