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

The description adds substantial behavioral context beyond the annotations: it discloses cost ($0.02), the x402 payment flow including the first-call payment-terms behavior, expected latency (~3-20 s), and that processing runs on Lordevo's local model rather than cloud AI. It also lists the public signals used, giving the agent a clear sense of what the tool evaluates.

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 description is dense but mostly earns its length by covering payment, outputs, signals, processing model, and latency. It is less front-loaded than ideal because it opens with pricing and payment mechanics before stating the core purpose, but the information remains useful and organized in a single readable paragraph.

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 adequately explains return values: verdict labels, a 0-100 trust score, and short reasons. It also covers cost, payment flow, and latency, but does not describe failure modes or what happens for unreachable or invalid URLs, leaving a minor gap.

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?

There is only one parameter, and the input schema has 100% description coverage, fully defining the url field as a public http(s) URL or bare domain. The description does not add further URL syntax or validation semantics, so the baseline of 3 is appropriate.

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 clearly states the resource and outcome: an AI trust verdict for a website, with concrete labels (likely_legit / caution / suspicious), a 0-100 score, and short reasons. It distinguishes itself from sibling audit tools by focusing on legitimacy/trust signals rather than general SEO, security, or page metadata, though it does not explicitly name those alternatives.

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?

Usage is implied by the title and description: use this when you need a trust/legitimacy verdict for a website. However, there is no explicit when-to-use guidance versus siblings such as security_scan_lite, page_quality, or site_snapshot, and no stated exclusions or conditions.

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