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

Beyond the read-only and open-world annotations, it discloses parallel page retrieval, the number of pages read, the cited-excerpt output, the exact $0.08 USDC price, supported networks, the X-PAYMENT requirement, and free-trial exclusion. These details provide substantial operational and cost transparency.

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?

Four compact sentences front-load the core behavior and output, then cover payment and the optional answer mode. There is no filler or redundant restatement of 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?

The description covers the workflow, output, and commercial prerequisites despite the absence of an output schema, making it broadly usable. However, the sparse input schema leaves important invocation ambiguities, and the lack of sibling routing limits complete selection guidance.

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?

With 0% schema description coverage, the description explicitly explains only answer and indirectly conveys n through the 3-8 page range. The distinction between q and query remains ambiguous, especially with no required parameters, and maxChars is not explained.

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 opening sentence specifies a concrete workflow and deliverable: search the web, read 3-8 top pages in parallel, and return a cited brief with excerpts. It does not explicitly distinguish this from siblings such as web_search, search_extract, or answer.

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 conditional guidance to set answer: true for an LLM-written cited answer and states payment and free-trial constraints that affect whether the tool can be used. It does not explain when this deeper, paid workflow is preferable to simpler search or extraction siblings.

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