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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds genuinely useful context beyond them: the exact 0-99 score output with AI reasoning, and the $0.25 USDC x402 payment requirement, which is critical for an agent to know before calling.

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?

Two tight sentences: purpose and return value first, then use cases, then cost. Every clause carries information an agent needs, 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?

With no output schema, the description correctly compensates by describing the return value (0-99 score plus AI reasoning). Parameters are fully covered by the schema. Minor omission: no note on behavior for unknown or ambiguous company names.

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 both parameters (lookup, language enum) are fully documented in the schema. The description mentions neither the company-name input nor the optional language parameter, so it adds no meaning beyond the structured fields; baseline 3 applies.

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 and resource ('checks whether a company or organization is real') and specifies the returned artifact: a 0-99 legitimacy score plus AI-generated reasoning. It distinguishes itself in substance from firmographic siblings like business_info by emphasizing verification, but it never names an alternative explicitly.

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?

Enumerates concrete use cases — KYB, vendor/supplier onboarding, fraud prevention, B2B signup screening — which gives an agent a clear picture of when to reach for it. It stops short of stating exclusions or pointing to a sibling for adjacent needs (e.g., firmographic enrichment).

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