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

Goes well beyond the annotations by disclosing the register's noisy token search, the re-checking logic that only reports exact matches (or ones differing solely in legal form) as 'found', and the fallback of returning candidates. It also states the pricing/auth model ($0.005/call via x402, x-credit-token header, 1 free call/day, no API key), which is essential operational context.

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-loads the core question and answer before the mechanics, and every clause (matching behavior, pricing, auth) carries weight. It is dense and slightly long, but no sentence is 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 an output schema present and 100% parameter coverage, the description needn't explain return values, yet it still enumerates them for orientation and fully covers input, matching behavior, and cost. Nothing needed to call it correctly is missing.

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?

Only one parameter exists and schema coverage is 100%, so the schema already documents it fully; the description adds only 'Required input: name'. Baseline 3 is appropriate, though the matching-semantics explanation gives marginal extra value.

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 ('look a company up in GLEIF, the global Legal Entity Identifier register') and enumerates the returned fields (LEI code, legal name, entity status, jurisdiction, address). This clearly distinguishes it from nearby siblings like sanctions_name, compliance_check, and bic_check.

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 framing question 'Does this company legally exist, and where?' plus the explanation of GLEIF's token search gives strong context for when to reach for it. However, it never names an alternative tool or an explicit when-not condition, so it stops short of full routing guidance.

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