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

With annotations present, the description still adds substantial context: pricing ($0.01/call via x402 USDC or card key), failed calls free, repeated calls charged (consistent with idempotentHint=false), and Brave API terms restricting reuse of results. It also discloses the verdict vocabulary and the output shape (explanation, [n] citations, sources).

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 what the tool does and returns, then caveats, then use case, then pricing. Dense but nearly every sentence carries operational information; the price/payment sentence is long but justified for an agent deciding whether to call.

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?

There is no output schema, and the description compensates by describing the return: a verdict from a fixed set (supported, contradicted, mixed, unverified), a short explanation, numbered citations, and the sources. Nothing an agent needs to decide or interpret the call 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?

Schema coverage is 100% and there is only one parameter, so baseline is 3. The description adds an example claim ('The x402 protocol uses the HTTP 402 Payment Required status code.') that shows the expected granularity, going slightly beyond the schema's length constraint.

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?

States a specific verb and resource (check a claim against the live web) and spells out the pipeline (Brave search, page reads, Llama 4 Scout verdict). No sibling tool in the list does fact verification, and the description makes that unique role obvious.

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?

Gives a concrete trigger: 'Use to screen a statement before an agent repeats or acts on it.' It also sets expectations with 'A model's reading of a few search results, not an editorial fact-check.' It doesn't name an alternative tool for cases where a plain answer (ai_answer) would suffice, so it stops short of explicit alternative routing.

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