Validate a single email address with comprehensive checks: syntax (RFC 5322), MX records, disposable domain detection, role-based detection, SPF/DKIM, typo suggestions, and risk scoring (0-100).
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | Email address to validate |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden and lists a detailed set of checks (syntax, MX, disposable, role-based, SPF/DKIM, typo suggestions, risk score). This is transparent about what the tool does, but it omits details about the return structure, potential errors, and network dependencies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the core action ('Validate a single email address') and efficiently lists all validation aspects without redundancy. Every phrase adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a simple one-parameter tool with no output schema, the description provides a thorough overview of the validation logic and a risk score range. It could be more complete by stating what the return value looks like (e.g., a result object), but the listed checks and score range give enough context for typical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully describes the only parameter ('email') with a clear definition. The description adds no parameter-specific meaning beyond the validation checks, but since schema coverage is 100%, it does not need to compensate. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool validates a single email address and lists specific checks, distinguishing it from siblings like validate_batch (batch) and check_domain (domain-only). The verb 'validate' plus resource 'email' is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes clear it is for single email validation with comprehensive checks, implying it should be used when detailed validation is needed rather than simple domain checks or batch processing. However, it does not explicitly name alternative tools or state when not to use it, so it lacks strong exclusion guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.