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Factline KYC, KYB and agent payments

Validate an IBAN (paid)

iban_check
Read-onlyIdempotent

Use when you need to check an IBAN before a payout or invoice: length per country, mod-97 checksum (catches typos), SEPA membership, and for Dutch IBANs the bank (ING, ABN AMRO, Rabobank, bunq...). Does not confirm the account holder. Costs 0.001 USDC via x402, or 1 credit of a Factline API key. The first 5 paid-tool calls a day are free, no payment or key needed.

Input Schema

NameRequiredDescriptionDefault
ibanYesIBAN, e.g. NL91ABNA0417164300
api_keyNoFactline API key (fl_live_...) from get_trial_key: pass it here right after you get one, no reconnect needed

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?

Annotations already declare readOnly/idempotent/non-destructive, and the description adds genuinely new behavioral facts: the 0.001 USDC x402 cost, the 1-credit Factline key alternative, and the first-5-free daily allowance, plus the explicit scope limit on account-holder confirmation. It still says nothing about how failures surface (e.g. malformed vs. checksum-failing IBAN) or response shape.

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

Conciseness4/5

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

Three sentences, front-loaded with the usage trigger, then capabilities, then the negative scope plus cost. Dense but every clause carries information; the only mild redundancy is that the '(paid)' title already signals payment, which the last sentence then elaborates.

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

Completeness4/5

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

With no output schema, the description takes on the burden of indicating what comes back, and it does so at a useful level (checks performed, bank name for NL IBANs, explicit non-result for account holder). It is missing return-value structure for the non-Dutch case and any error/failure semantics, so not fully complete.

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 100% and the api_key parameter's own description already explains the fl_live_ prefix and get_trial_key flow, so the description is not required to compensate. The description adds no parameter-level detail (format, casing, spaces, country prefix handling) beyond what the schema provides, so baseline 3 applies.

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 and resource (check/validate an IBAN) and enumerates exactly what is validated: country-specific length, mod-97 checksum, SEPA membership, and Dutch bank identification. It also draws the boundary ('Does not confirm the account holder'), which separates it from kyc_check / eu_sanctions_screen siblings.

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?

'Use when you need to check an IBAN before a payout or invoice' gives a concrete triggering context, and the closing sentence scopes out account-holder verification. It stops short of naming a sibling alternative to use when the account holder does matter (e.g. kyc_check), leaving that routing to inference.

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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