query_gemini

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

With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: supports conversation history for multi-turn interactions, streaming enabled by default for better responsiveness. It doesn't mention rate limits, authentication needs, or error behaviors, but provides substantial operational context.

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 well-structured and front-loaded with the core purpose, followed by usage guidelines and behavioral details. Every sentence earns its place - no redundant information, and the bulleted list efficiently communicates usage scenarios without 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?

For a query tool with no annotations and no output schema, the description provides good context about when to use it and behavioral characteristics. It could be more complete by mentioning response format, error handling, or model selection options, but covers the essential operational aspects well given the complexity.

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 baseline is 3. The description adds minimal parameter semantics beyond the schema - it mentions 'conversation history for multi-turn interactions' which relates to the history parameter, but doesn't provide additional context about prompt construction or streaming implications beyond what's in the schema descriptions.

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 as 'Query Google's Gemini AI models for text generation, reasoning, and analysis tasks' - a specific verb+resource combination. It distinguishes from sibling tools (count_gemini_tokens, list_gemini_models) by focusing on querying rather than token counting or model listing.

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 explicit usage scenarios in a bulleted list: 'Get a second opinion or alternative perspective', 'Leverage Gemini's specific capabilities', 'Generate content using a different AI model', and 'Compare responses between AI models'. These give clear guidance on when to use this tool versus alternatives.

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