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generate_iban

Generate one or more random, structurally valid (ISO 13616 / MOD-97) test IBANs for a country, with correct national check digits where the country has them. Generated IBANs were not issued by any bank: never use them for payments.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo
countryYesISO 3166-1 alpha-2 country code, e.g. DE, FR, IT.
realisticNoRealistic mode (default true): digits only in alphanumeric fields (except real bank codes that contain letters), and a real bank code of a major bank (where curated data exists for the country) with a random account number. Pass false for fully random bank codes and accounts (letters where the format allows them). Such an IBAN was not issued by any bank but could match a real account by chance, so never use it for payments.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

No annotations, so the description carries the full burden and does most of it: it discloses randomness, the ISO 13616/MOD-97 validity guarantee, correct national check digits 'where the country has them', and the critical caveat that generated IBANs were never issued by a bank. It omits return shape and any determinism/rate-limit behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two dense sentences with zero filler; the validity guarantee and the payment prohibition are both front-loaded where an agent will read them.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no annotations and no output schema, the description should say what comes back (single string vs. array when count > 1). It covers behavior well but leaves the return contract unstated, which matters for a tool whose count parameter ranges 1-100.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 67%; country and realistic are well documented in the schema, and the description only echoes 'for a country' and 'one or more' (count). It adds no meaning beyond the schema for any parameter, which is the expected baseline at this coverage level.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (generate) and resource (random, structurally valid ISO 13616 / MOD-97 test IBANs) with clear scope qualifiers. The 'generate' verb cleanly separates it from sibling validate_iban and list_countries without needing to name them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Frames the use case explicitly as test data ('test IBANs') and gives a hard prohibition ('never use them for payments'), which is genuine when-not guidance. It stops short of routing to siblings (e.g. use validate_iban to check a real IBAN), so it isn't a full 5.

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

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