answer

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

Annotations already indicate readOnly, openWorld, idempotent, and non-destructive behavior. The description adds valuable behavioral context beyond those: it discloses cost per call, wallet requirement, grounding in live web search, and the fact that results come from an independent search index rather than training data. This gives the agent meaningful operational expectations without contradicting annotations.

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 compact, front-loaded with cost and prerequisites, and uses three sentences to cover functionality, output format, and ideal use case without redundancy. Every sentence adds useful information, and nothing is wasted.

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 rich annotations, complete schema coverage, and presence of an output schema, the description provides sufficient context for an agent to decide whether and how to invoke the tool. It explains what the tool returns, how it works, what it costs, and when to use it. No critical information needed for correct invocation is missing.

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 input schema has 100% parameter documentation coverage, so the description does not need to restate parameter meanings. The description adds little to parameter understanding beyond framing q as a natural-language question and implying that max_tokens controls answer length, but this is already covered. With full schema coverage, a baseline of 3 is appropriate.

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 function: generating an AI answer to a natural-language question grounded in live web search with citations. It distinguishes itself from a raw search tool by emphasizing 'clean prose plus a structured citations array' and an 'independent search index, not the model's training data.' This makes the purpose unmistakable and separates it from web.search and similar siblings.

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 gives clear context on when to use the tool: 'when an agent needs a synthesized answer plus the receipts to verify or follow up.' However, it does not explicitly mention when not to use it or contrast it with specific alternatives such as web.search or web.news, stopping short of a full 5.

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