ask_gemini

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the 1M token capacity and model options (free/fast vs paid/better quality), which adds useful context about capabilities and cost implications. However, it doesn't cover rate limits, error handling, response format, or authentication requirements that would be important for a tool like this.

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 perfectly concise with two sentences that each earn their place. The first sentence establishes the core purpose and key differentiators, while the second provides the essential usage guidance. 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?

Given the tool's complexity (AI model interaction with large context), lack of annotations, and no output schema, the description is adequate but has clear gaps. It covers the main use cases and capacity but doesn't address response format, error conditions, or operational constraints that would be important for complete understanding.

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 documents all three parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. The baseline of 3 is appropriate when the schema does the heavy lifting for parameter documentation.

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 with specific verbs ('use Gemini for large context analysis, architecture design, or whole codebase review') and distinguishes it from siblings by emphasizing its suitability for tasks requiring understanding of entire projects, unlike image generation tools or potentially more focused code analysis tools.

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 clear context for when to use this tool ('large context analysis, architecture design, or whole codebase review'), but doesn't explicitly state when NOT to use it or name specific alternatives among the sibling tools. It implies usage for extensive tasks but lacks explicit exclusions.

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