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

With annotations already covering safety (readOnly, idempotent, openWorld), the description adds the traits annotations cannot: cost of 0.003 USDC via x402, a 2-credit alternative via a Factline API key, and a free allowance of the first 5 paid-tool calls per day. It also shows the shape of the result — a low/medium/high risk rating with human-readable flags like 'registered 4 days ago' — which tells the agent what evidence to expect.

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 trigger condition is front-loaded and the paragraph is dense with facts rather than filler. It is a long single sentence-chain, though; splitting the cost/payment sentence from the capability sentence would improve scannability.

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?

No output schema exists, so the description has to convey the return shape itself, and it does by naming the risk tiers and example flags. Payment prerequisites are stated, which is critical for a paid tool. The response structure beyond the risk label is still sketched only in outline, leaving minor gaps for an agent planning to consume the output.

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 'domain' parameter is already documented as accepting a domain, URL, or email. The description repeats that accepted input set ('Accepts a domain, URL or email') without adding normalization rules, format constraints, or invalid-input behavior. Baseline 3 applies since the schema does the heavy lifting.

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 opens with a specific verb and resource ('judge whether a website or email domain is trustworthy') and then enumerates the exact signals returned — RDAP registration date, expiry, registrar, nameservers, MX/SPF/DMARC, disposable-domain lists, and a graded risk level. That is far more precise than the bare tool name. It doesn't explicitly name a sibling like email_verify to say how it differs, which keeps it below a 5.

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 you need to judge whether a website or email domain is trustworthy' gives a clear triggering condition and scope. It doesn't state exclusions or point to alternatives such as email_verify or company_lookup, so boundary cases are left to inference.

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