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Temsor API — Turkey & EU business data

IBAN Validation

iban_validate

Validates an IBAN from any of 70+ countries: checksum, country length and in-country account structure, and resolves the bank and branch codes.

Most free libraries stop at the mod-97 checksum. That only says the digits are self-consistent — not that the number could exist in that country. This checks the country's BBAN structure too, so a wrong-length or wrong-shaped account is rejected before your payment file reaches the bank. When only the two check digits are wrong, the correct ones are computed and returned as a suggestion, because that is what people actually mistype. Turkish, Dutch and Belgian IBANs additionally resolve to a bank name when the national code is in our table; otherwise bankName is null. This is not a SWIFT directory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ibanYesIBAN, with or without spaces.
expectCountryNoExpected country code (ISO 3166-1 alpha-2).

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden. It explains how the tool differs from mod-97-only validators, that it checks BBAN structure, that corrected check digits are suggested, and that bankName can be null. A slight internal inconsistency exists between 'bank and branch codes' and the later explanation only mentioning bankName, but overall behavior is well disclosed.

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 concise and front-loaded with the core action. Each subsequent sentence adds meaningful information — why stronger validation matters, correction behavior, bank-name limitations, and what the tool is not. No wasted words or repetition.

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?

Given that there is no output schema, the description compensates by explaining corrective suggestions, null bankName values, and country-specific resolution. It could be more explicit about the exact return fields, but the key behavioral context is present and sufficient for an agent to select and interpret the tool.

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?

Both parameters (iban and expectCountry) are fully described in the input schema, so the description's lack of extra parameter-level detail is acceptable. It adds no new semantic or syntax information beyond schema coverage, earning the baseline 3.

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?

Opening sentence clearly states the tool's purpose: 'Validates an IBAN from any of 70+ countries: checksum, country length and in-country account structure, and resolves the bank and branch codes.' This names a specific verb, resource, and scope, distinguishing it from the many sibling validation tools by focusing exclusively on IBANs.

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?

The description gives clear context about when this tool exceeds basic checksum validation and warns against interpreting it as a SWIFT directory. It does not explicitly name alternative tools or state 'when not to use', but the limitations and unique added value are clearly implied.

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

A4/5.0
Disambiguation4/5

Most tools have clearly distinct purposes (e.g., bic_validate vs vin_validate), but there is notable overlap: tr_validate bundles Turkish validations that are also covered individually by iban_validate and tin_validate. Also, lei_validate and lei_lookup are closely related but distinct enough. Overall, agents can usually pick the right tool, but a few pairs could confuse.

Naming Consistency4/5

Tool names are consistently snake_case with predominately verb_noun patterns (e.g., validate, lookup, screen, parse, build). Some nouns like mcp_index, model_archive, and series_history break the verb pattern but are still predictable. Minor deviations from the noun_verb form (tr_invoice_build, shipping_identify) don't cause confusion. Very readable and consistent overall.

Tool Count3/5

With 27 tools, the set is heavy, exceeding the typical 3–15 well-scoped range. However, the server covers a broad domain: international standards validation, Turkey-specific business data (fuel, labor, invoices, addresses), and even MCP/LLM model archives. The count is justifiable given the scope, but it stretches coherence and may overwhelm agents.

Completeness4/5

The tool surface is remarkably comprehensive for the stated Turkey & EU business data purpose: validators for most ID types, VAT, IBAN, phone, VIN, sanctions; plus Turkey-specific operations like invoice build/parse, labor calculations, fuel prices, business days, and address parsing. Minor gaps exist (e.g., no general exchange-rate conversion, no credit-note-specific builder), but agents can accomplish core workflows without dead ends.

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