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

With no annotations, the description carries the behavioral burden and does it well: it discloses cost ($0.02 USDC per call) and the payment mechanic (returns x402 payment requirements; the wallet executes payment). That payment/cost detail is genuinely useful and not captured by any structured field. It does not mention rate limits or failure modes, keeping it short of a 5.

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 purpose, then cost, then return/payment behavior, then a concrete example. Every sentence earns its place with no filler.

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?

An output schema exists, so return-field explanation is not required, and the description still lists the extraction surface plus cost and payment flow. It is nearly complete for a single-parameter paid tool, missing only edge/error behavior.

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 0% and there is only one parameter, so the description must supply format meaning. The example contact_page(domain="acme.com") usefully shows the parameter is a bare domain string, but it doesn't clarify whether paths, schemes, or subdomains are accepted.

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 precise verb+resource ('Extract a company's published contact surface from its own public website') and enumerates the concrete outputs (emails role vs personal, phones, contact-form presence, address, social links). An agent can immediately distinguish this from siblings like email_pattern, lookup_lead, or dns.

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 scope ('from its own public website') is clear, but there is no explicit when-to-use or when-not guidance relative to siblings such as lookup_lead or email_pattern. Usage is implied by what it extracts rather than stated.

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