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

Goes well past the annotations (readOnly/openWorld/non-idempotent) to disclose pricing ($0.01/call, failed calls free), payment paths (x402 USDC or card key), a legal restriction on storing/resale/training, and the failure mode ('Says so when the sources do not answer it'). The non-idempotent, charged-per-call economics are surfaced explicitly, which is exactly the context annotations cannot carry.

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 capability and output format before terms and pricing, and nearly every clause carries decision-relevant information. Minor redundancy: 'each call is charged, so repeats are not free' restates the earlier price line and the readOnly safety claim is largely covered by the annotations.

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?

With no output schema, the description carries the full return-value burden and does: citations format, source list contents, and the negative case when sources are insufficient. Cost, licensing, and safety are all present — an agent has everything needed to call it correctly.

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 the single parameter already documents the 400-character limit, so the schema does the heavy lifting. The description adds only an example question string, which illustrates shape but not semantics beyond the 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?

States a specific verb+resource ('Answer a question from the live web') and enumerates the internal pipeline (Brave search, top pages read, Llama 4 Scout synthesis) plus the output shape (inline [n] citations, source list). Clearly separable from siblings that return raw text or raw search results.

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?

'Use when an agent needs a current, sourced answer rather than raw search results' gives an explicit selection rule, and the worked example (q=What is the x402 payment protocol?) anchors it. It stops short of naming specific sibling alternatives such as ai_fact_check or ai_chat, so an agent must infer the boundary itself.

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