Temsor API — Turkey & EU business data

LEI Validation

lei_validate

Validates a 20-character Legal Entity Identifier (ISO 17442) with the ISO 7064 mod-97 check digits.

KYC and MiFID reporting reject an LEI that fails the check digits before anyone looks the entity up. The algorithm is the same family as IBAN (ISO 7064 mod 97-10) over all 20 characters; the remainder must be 1. The first 4 characters are the issuing LOU prefix, the next 14 the entity, the last 2 the check digits. This does not call GLEIF. A checksum-valid LEI can be lapsed, merged, or never issued. Use GLEIF's free API if you need "this legal entity is currently registered".

Input Schema

TableJSON Schema

Name	Required	Description	Default
`lei`	Yes	Legal Entity Identifier, 20 characters.

TDQS

A4.7/5.0

Behavior5/5

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

With no annotations, the description carries the full burden and does well. It explains that the tool performs checksum validation only, does not call external services, and clarifies that a valid checksum does not guarantee registration. This transparently sets expectations about side effects and limitations.

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 concise without being terse. It is well-structured: a clear purpose statement, a practical rationale, algorithm details, and a caveat about registration. While slightly verbose, each sentence adds relevant information and avoids redundancy.

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 no output schema, the description does not need to explain return values. It covers the tool's behavior, limitations, and alternative usage, making it sufficient for an agent to decide when to call it. Minor omissions like error handling are not critical for a validation tool.

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?

The schema description already specifies 'Legal Entity Identifier, 20 characters,' providing basic semantics. The tool description adds valuable detail about the LEI structure (first 4, next 14, last 2) and the checksum algorithm, enhancing the understanding of the parameter beyond the 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 the tool's purpose: 'Validates a 20-character Legal Entity Identifier (ISO 17442) with the ISO 7064 mod-97 check digits.' It also distinguishes it from other validators by focusing on LEI and explicitly notes that it does not call GLEIF, which is a separate concern.

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?

The description provides explicit usage guidance: it is suitable for 'KYC and MiFID reporting' when a checksum check is needed, and it advises using GLEIF's API if registration status is required. This clearly differentiates when to use this tool versus alternatives.

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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