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batch_validate_iban

Validate up to 100 IBANs in a single call at 10x cheaper cost per IBAN. Ideal for cleaning CSV files or triaging payout lists.

Instructions

Validate up to 100 IBANs in a single call (10x cheaper per IBAN than calling validate_iban repeatedly). USE WHEN: the user pastes a list of IBANs, asks to clean a CSV/spreadsheet of bank accounts, asks to dedupe a customer database, asks to triage a payout list before sending, or whenever you would otherwise call validate_iban more than 2-3 times in a row. RETURNS: array of per-IBAN results (same shape as validate_iban) + a summary { total, valid, invalid, by_country, by_issuer_class }. COST: 0.002 USDC per IBAN, max 0.20 USDC for 100 IBANs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ibansYesArray of IBAN strings (1 to 100 entries).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultsYesOne entry per input IBAN, in the same order. Same shape as validate_iban output.
summaryYes
cost_usdcNoActual USDC charged for this call.
Behavior4/5

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

Despite no annotations, the description discloses behavior: validates IBANs, returns per-IBAN results plus summary, and specifies cost (0.002 USDC per IBAN, max 0.20 USDC). It does not mention side effects or authentication needs, but as a stateless validation, this is sufficient.

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?

Three concise, information-dense sentences: purpose, usage scenarios, and return details. No wasted words, front-loaded with key value proposition.

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

Completeness5/5

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

Given the presence of an output schema and single parameter, the description covers usage, returns, and cost completely. For a batch validation tool with clear context, no gaps remain.

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%; the single parameter 'ibans' is described in schema. The description adds cost context but no new parameter semantics, so baseline 3 is appropriate.

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?

The description clearly states the tool validates up to 100 IBANs in a single call, highlighting efficiency and cost savings compared to repeated single IBAN calls. It distinguishes itself from sibling tool validate_iban by specifying batch capability.

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

Usage Guidelines5/5

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

Explicit 'USE WHEN' section lists specific scenarios like pasting a list, cleaning CSV/spreadsheet, deduping database, or triaging payout lists. Also advises not to call validate_iban more than 2-3 times consecutively, providing clear when-to-use and when-not-to-use guidance.

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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