Global legal-entity/KYB lookup by LEI: official identity, jurisdiction, addresses, registration and renewal standing, risk flags, and GLEIF data freshness. Paid per call: $0.008 in USDC via x402.
| Name | Required | Description | Default |
|---|---|---|---|
| lei | Yes | 20-character Legal Entity Identifier (path parameter); checksum is verified before payment |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden. It transparently discloses that the tool is paid per call ($0.008 USDC via x402), which is a critical behavioral trait. It also lists the data categories returned, giving context on what the call accomplishes. It does not mention rate limits or failure modes, but for a paid lookup tool, the cost disclosure is substantial.
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 a single, information-dense sentence. It front-loads the purpose and then efficiently lists data types and pricing. Every clause adds value with no redundant wording.
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 simple one-parameter lookup with no output schema, the description provides a comprehensive list of data categories and cost information. It lacks response structure details, but the data category list offers adequate context for an agent to decide if the tool meets the user's need. The payment detail is also valuable.
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%; the parameter 'lei' is fully described in the schema (format, pattern, checksum verification). The tool description adds no additional parameter-level semantics beyond what the schema already provides, so baseline score of 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?
The description opens with 'Global legal-entity/KYB lookup by LEI' which clearly identifies the specific verb (lookup) and resource (legal-entity/KYB data). It distinguishes itself from siblings like dns, qr, and vat by focusing on LEI-based entity lookup and enumerates the returned data types (official identity, jurisdiction, addresses, registration status, risk flags, GLEIF freshness).
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 description implies usage context: when you have an LEI and need legal-entity or KYB data. It does not explicitly state exclusions or alternative tools, but the clear scope and mention of payment may implicitly signal to use only when necessary. However, no explicit 'use X instead' guidance is present.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool addresses a distinct function: DNS resolution, email authentication, web extraction, legal entity lookup, QR generation, RDAP lookup, robots.txt parsing, sitemap parsing, text cleaning, and VAT calculation. There is no overlap or ambiguity between them.
All tool names are lowercase, concise, and use hyphens for compound words. Although some are nouns and some verbs, the style is uniform and each name clearly indicates its purpose, following a predictable convention.
With exactly 10 tools, the set is well-scoped for a general web utility server. Each tool covers a distinct need, and the count falls comfortably within the optimal 3-15 range.
The tools cover a comprehensive range of DNS, WHOIS, and domain-related functions, including DNS lookup, RDAP registration data, email auth, robots.txt, and sitemaps. The additional utilities (extract, text-clean, QR, LEI, VAT) round out the server without leaving obvious gaps in its stated purpose.
