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Temsor API — Turkey & EU business data

E-mail Verification

email_verify

Checks an e-mail address: syntax, whether the domain can actually receive mail, disposable and role-account detection, and typo correction.

No SMTP probing. Most competitors connect to the target server and try RCPT TO, which sounds thorough but produces a confident-looking number you cannot trust: most servers are catch-all, the big providers refuse to answer, and doing it in bulk gets the probing IP blacklisted. We report only what is provable — whether the domain has a mail exchanger, whether it is a known disposable service, whether the mailbox belongs to a role rather than a person, and whether the domain looks like a typo of a common one (gmial.com → gmail.com). Addresses are also normalised, so Gmail dots and +tags stop creating duplicate signups.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailYesE-mail address to check.
rejectRoleAccountsNo
rejectFreeProvidersNo

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses all verification checks (syntax, domain mail exchanger, disposable, role, typo) and normalization, and explicitly states the absence of SMTP probing. It does not cover authentication needs or rate limits, but provides sufficient behavioral details.

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 informative but slightly verbose. It front-loads the main purpose and then explains the rationale. Every sentence adds value, though some trimming could improve conciseness.

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 the 3 parameters, no output schema, and no annotations, the description provides a good level of context about what the tool does and its methodology. It lacks details on output format and error handling, but is reasonably complete for a verification 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?

Schema description coverage is low (33%), so the description must compensate. It explains the 'email' parameter by detailing the checks performed, but does not explicitly link the boolean parameters 'rejectRoleAccounts' and 'rejectFreeProviders' to their functions, though 'role-account detection' and 'disposable service' are mentioned. Adds some value but could be more explicit.

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 specifies a clear verb ('checks') and resource ('e-mail address'), and lists multiple verification aspects (syntax, domain mail receipt, disposable detection, role detection, typo correction, normalization). It distinguishes itself from competitors by explicitly stating what is not done (no SMTP probing).

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 explains what the tool does and does not do, and provides reasoning for its approach. It implicitly suggests when to use it (when reliable verification without SMTP probing is needed) but does not explicitly mention alternative sibling tools or 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

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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