list-models

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

There are no annotations, so the description carries the burden of explaining behavior. 'List' conveys a read-only intent and no destructive side effects are implied or hidden. However, it does not disclose any additional behavioral details such as authentication requirements, rate limits, or whether the list is cached.

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 delivers the essential information with no filler. The action, resource, and context are all front-loaded and every word is meaningful.

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 zero-parameter list tool with an output schema, this description is nearly complete. It identifies what the tool surfaces and the service context. The only notable gap is the lack of guidance about how this fits into the workflow alongside sibling tools, but the low complexity limits the impact of that omission.

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 the schema coverage is effectively complete, so no parameter-level explanation is needed. With 0 params, the baseline is 4, and the description does not need to compensate for any schema gaps.

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 uses a specific verb ('List') and resource ('available models') scoped to 'Google Antigravity', making the tool's purpose immediately clear. It also stands apart from the sibling tools, which focus on asking, reviewing, checking, generating, and pinging.

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 guidance is provided about when to use this tool versus the alternatives. An agent can infer it is a preliminary discovery step before using ask-antigravity or ask-gemini, but the description does not state this explicitly.

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