query

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

With no annotations, description carries the burden. It discloses multi-turn execution, automatic tool use, and multimodal support, but omits safety traits like cost, rate limits, error handling, or latency.

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?

Front-loaded with main purpose, followed by key capabilities. Minor redundancy (e.g., multi-turn and multimodal mentions), but overall efficient and well-structured.

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?

Covers core functionality but lacks output format details (e.g., response structure) and limits on tool calls. Given complexity and no output schema, more detail would improve completeness.

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%, so baseline 3 applies. Description adds no extra meaning beyond schema descriptions (e.g., model, parts, sessionId are already explained in schema).

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?

Description clearly states it queries Google AI (Gemini models) with a prompt, specifying it as an intelligent agent with multi-turn and multimodal capabilities. It differentiates from sibling tools like 'search' (direct search) and 'generate_image' (media generation) by emphasizing agentic reasoning and automatic tool use.

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?

Description implies usage for complex queries requiring multi-step reasoning and automatic tool use, contrasting with siblings. Context is clear but lacks explicit when-not scenarios or direct comparisons, e.g., when to use 'search' instead.

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