ask_antigravity

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

No annotations are provided, so the description bears full transparency burden. It discloses that the tool reads entire files/folders when paths are given, uses a default model (Gemini 3.1 Pro High), and provides an independent perspective. However, it omits operational details like error handling or response format.

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 concise, well-organized, and front-loaded with the main value proposition. Every sentence serves a purpose without redundancy or verbosity.

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 tool's complexity (three parameters, no output schema), the description covers the main semantics and usage context. It could mention that the response is free-form text or provide example output, but it is sufficient for an agent to understand the tool's function.

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 the description adds meaning beyond each parameter's schema description. It explains that 'paths' are read as full context, 'model' defaults to a specific model, and 'prompt' is the user's request. This clarifies usage well.

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: to get an independent second opinion or code review from a different model family (Google Antigravity/Gemini 3.1 Pro High). It uses specific verbs like 'validate', 'review', and distinguishes from Claude by emphasizing cross-check value.

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 explicitly lists ideal scenarios: validating an approach before coding, getting an alternative design, or reviewing code for bugs/edge cases/style. It implicitly differentiates from using Claude by noting the cross-check benefit, but does not explicitly state when not to use it.

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