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email-validator

check_domain

Check domain reputation: MX records, SPF, DKIM, disposable detection, A record existence, and overall reputation score.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesDomain to check (e.g. gmail.com)

TDQS

B3.2/5.0
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 transparency burden. It discloses the checks performed but omits any behavioral traits such as whether the operation is read-only, network dependencies, potential delays, permission requirements, or output format details. Only the verb 'check' implicitly suggests non-mutation.

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 a single, front-loaded sentence that efficiently lists the checks without extraneous words. It earns its length by providing concrete detail about the tool's scope.

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?

For a simple single-parameter tool, the description adequately conveys the tool's purpose and scope. However, with no output schema, it doesn't explain the return format, score ranges, or potential error conditions, leaving some ambiguity for an agent deciding whether this tool meets its needs.

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 covers 100% of the single parameter ('Domain to check (e.g. gmail.com)'). The description adds context about what checks the domain undergoes, which slightly enriches the parameter's meaning, but it doesn't provide additional format or validation details. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Check domain reputation') and specifies the exact resources checked (MX, SPF, DKIM, disposable detection, A record existence, reputation score). It distinguishes itself from sibling validate_email by focusing on domain-level checks, though it doesn't explicitly name the sibling.

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 usage when domain-level reputation verification is needed, listing specific checks. However, it provides no explicit when-to-use vs. alternatives like validate_email or suggest_fix, nor any exclusions or prerequisites. The implied context is clear but not fully developed.

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

A3.7/5.0
Disambiguation2/5

validate_email includes comprehensive checks (syntax, MX, SPF/DKIM, typo suggestions, risk scoring) that subsume both check_domain and suggest_fix, making the targeted tools redundant for many use cases. validate_batch is clearly separate, but the overlap between the individual validation tools and the single comprehensive validator creates ambiguity.

Naming Consistency4/5

All tool names follow a consistent verb_noun snake_case pattern (check_domain, suggest_fix, validate_batch, validate_email). The verbs differ appropriately for their actions, though validate_batch and validate_email share the same verb while the others use distinct verbs, which is a minor deviation but still predictable.

Tool Count5/5

With 4 tools, the server is well-scoped for an email validation service. Each tool has a clear purpose (single validation, batch validation, domain reputation, typo suggestions), and the count is neither sparse nor bloated.

Completeness4/5

The core email validation workflow is well covered: single check, batch processing, domain reputation, and typo correction. A minor gap is the lack of a dedicated syntax-only or MX-only validator, but validate_email already provides comprehensive checks, so most users will not encounter dead ends.