nano_banana_models

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

With no annotations, the description must convey safety. 'Return' clearly indicates a read-only operation, and mentioning 'usage notes' hints at practical constraints. It does not explicitly state that no side effects occur, but the semantic is clear enough for a listing tool.

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?

A single, concise sentence that front-loads the verb and resource. No wasted words or redundant information.

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?

The tool is simple with no parameters and an output schema, so the description's mention of both ids and usage notes is fully adequate. The sibling tool context further clarifies its role.

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 tool has zero parameters and schema coverage is 100%. The description adds no parameter details, but none are needed. A baseline of 4 is appropriate for a parameter-free tool.

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 a specific action ('Return') and a precise result ('supported Nano Banana model ids and usage notes'). It unambiguously identifies this as a listing/metadata tool, distinct from the sibling generation tool.

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?

No explicit guidance on when to use this tool versus nano_banana_generate_image is provided. The intended usage is implied (check available models before generation) but not directly stated, so the description earns a mid-level score.

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