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Validate IBAN, BIC or LEI

validate_identifier
Read-onlyIdempotent

Validate a single financial identifier (IBAN, BIC, or LEI) and receive a clear pass/fail result for quick verification.

Instructions

Validate a single financial identifier (IBAN, BIC, or LEI).

Use this for a one-off identifier check with a clear pass/fail. To validate
identifiers embedded across a whole batch of records, prefer
``validate_records`` rather than calling this per field.

Returns ``{"kind": str, "value": str, "valid": bool}``.

Args:
    kind: One of ``"iban"``, ``"bic"``, or ``"lei"`` (case-insensitive).
    value: The identifier value to check.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYesThe identifier type to validate: one of 'iban', 'bic', or 'lei' (case-insensitive).
valueYesThe identifier value to check, matching the chosen kind (e.g. an IBAN, an 8- or 11-character BIC, or a 20-character LEI). Whitespace/case handling follows the underlying validator.
Behavior4/5

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

Annotations already provide readOnly, idempotent, non-destructive hints. The description adds that the return format is a JSON object with kind, value, valid, which is not in annotations or output schema. No contradictions.

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?

The description is three sentences plus a code block and Args listing. It is reasonably concise and front-loaded with purpose. Could be slightly shorter, but no wasted words.

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?

For a simple validation tool with two parameters, comprehensive annotations, and no output schema, the description covers purpose, usage guidance, parameter semantics, and return format completely.

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

Parameters4/5

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

Schema description coverage is 100%, so baseline 3. The description adds clarification that 'kind' is case-insensitive and provides context on the value format (e.g., length of BIC/LEI), adding value beyond schema.

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 it validates a single financial identifier (IBAN, BIC, or LEI). It uses a specific verb ('Validate') and resource, and explicitly distinguishes from the sibling 'validate_records' by noting it's for one-off checks.

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?

Explicitly says when to use this tool (single identifier check) and when not (batch records), and directs to the alternative 'validate_records'. Also mentions the clear pass/fail outcome.

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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