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validate_iban

Validate IBAN (ISO 13616 mod-97) with SEPA BIC lookup for Portuguese banks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ibanYesIBAN string (with or without spaces)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral disclosure burden. It states the action but does not disclose return format, error behavior, network dependencies, external lookup side effects, or any prerequisites. The mention of 'SEPA BIC lookup' hints at external behavior but does not elaborate.

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?

The description is a single sentence, front-loaded with the primary action 'Validate IBAN', and contains no redundant information. Every word carries meaning, achieving high conciseness.

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?

The tool is simple with one parameter and no output schema, but the description does not explain what the tool returns (e.g., boolean, details) or the behavior of the BIC lookup. With no annotations or output schema, this is a clear gap, making the description merely adequate rather than 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% with a clear description for the 'iban' parameter ('IBAN string (with or without spaces)'). The description adds the ISO standard reference, which gives some context, but does not add significant meaning beyond the schema. The baseline 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's purpose: to validate an IBAN using the ISO 13616 mod-97 algorithm, with an additional SEPA BIC lookup for Portuguese banks. This specific verb plus resource and the standard reference clearly distinguishes it from siblings like validate_nif or verify_eu_vat.

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

Usage Guidelines3/5

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

The description implies when to use the tool (whenever IBAN validation is needed, especially for Portuguese banks with BIC lookup) but does not explicitly exclude alternatives or provide guidance on how to choose among sibling tools. No direct mention of when not to use it.

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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TDQS

A3.5/5.0
Disambiguation5/5

Each tool has a distinct purpose and target resource or operation. While some tools are thematically related (e.g., detect_secrets and classify_gdpr both analyze text), their specific outputs and use cases are clearly separated by names and descriptions.

Naming Consistency4/5

Most tools follow a clear verb_noun pattern (convert_currency, generate_uuid, validate_iban), and the noun_to_noun conversion tools (csv_to_json, html_to_text) form a consistent sub-pattern. The mix of verb_noun and X_to_Y is understandable and predictable, though not uniform.

Tool Count3/5

23 tools is on the higher end for a utility server, feeling like a grab-bag of many unrelated functions. While each tool is simple and serves a purpose, the count exceeds the typical well-scoped range, making it heavier than ideal.

Completeness3/5

The tool coverage is broad but scattered with no clear domain focus. Obvious complementary utilities are missing, such as URL encoding/decoding, YAML conversion, or PDF generation. However, within each small category, core operations are present, so agents can work around gaps.

Resources