generate_image

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions model characteristics (fast vs. high quality), it doesn't cover critical behavioral aspects like authentication requirements, rate limits, cost implications, file output behavior, or error handling. For a generative AI tool with no annotation coverage, this is insufficient.

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 extremely concise (two sentences) and front-loaded with the core purpose. Every sentence adds value: the first establishes the tool's function, and the second provides model differentiation. There's zero wasted text or redundancy.

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 complexity of an image generation tool with 6 parameters and no annotations or output schema, the description is incomplete. It covers the basic purpose and model options but lacks information about output format, file handling, error cases, or integration context. The schema handles parameter documentation, but the description should provide more operational 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?

Schema description coverage is 100%, so the schema already fully documents all 6 parameters. The description adds minimal value by briefly explaining the model options ('flash' for fast, 'pro' for high quality), but doesn't provide additional semantic context beyond what's in the schema. This meets the baseline of 3 when schema coverage is high.

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 purpose: 'Generate images using Google Gemini models.' It specifies the action (generate) and resource (images) with the technology context (Google Gemini models). However, it doesn't explicitly differentiate from the sibling 'list_images' tool, which would require a 5.

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 some usage context by explaining the two model options ('flash' for fast, 'pro' for high quality), which implies when to choose each. However, it doesn't explicitly state when to use this tool versus the sibling 'list_images' or provide any exclusion criteria or alternative scenarios.

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