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

Goes well beyond the annotations by disclosing the commercial terms an agent must know before calling: 0.05 USDC via x402, 25 credits with a Factline API key, and the first 5 paid calls per day free without payment or key. It also reveals the aggregation scope (10 registers plus sanctions/PEP lists) and the four possible verdicts, which annotations alone cannot convey.

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 the usage trigger and the scope list, and every clause carries real information (registers, screening targets, verdicts, input hints, pricing). The single dense run-on sentence packs several ideas together, making it harder to scan than it needs to be, but there is little waste to cut.

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?

For a zero-required-parameter, no-output-schema aggregation tool this covers purpose, inputs, cost, auth and the top-level verdict vocabulary, which is what an agent needs to decide and call. The gap is that the four verdicts are named but not defined (what makes a result 'review' vs 'incomplete', or what evidence accompanies the verdict), so the return shape stays partly implicit despite the missing output schema.

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%, so the baseline is 3, but the description adds a genuine retrieval hint not in the schema: 'best with country' signals the disambiguation strategy when only a name is supplied. It then names the optional qualifiers (vat, domain, kvk) that sharpen the match, though it adds no format or precedence rules beyond that.

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+resource ('European company check') and enumerates exactly what gets looked up: 10 named registers, sanctions/PEP screening of the company, directors, owners and parents, VAT/Peppol, websites, bankruptcies. This clearly separates it from narrower siblings like eu_vat_check, nl_insolvency_check or eu_sanctions_screen, which do only one of these things.

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?

Opening clause gives concrete triggering situations ('before onboarding, paying or contracting a European company'). It also tells the agent the best input shape ('name or id, best with country'). It stops short of naming alternatives among the 30 siblings — e.g. when to prefer company_lookup, company_dossier or kyc_check — so exclusions are absent.

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