Validate a single email address: RFC syntax check, MX record lookup on the domain, disposable/temporary-email-provider detection, and role-account detection (info@, admin@, etc.). Per-address check — different from email_deliverability_check, which audits a whole domain's sending reputation (SPF/DKIM/DMARC/PTR/DNSBL).
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | Email address to validate |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It does disclose the tool's behavior well: it performs four named checks, including a network-dependent MX lookup and role-account detection. It does not describe the return format or error behavior, but for a read-only validation tool the disclosed operation list is substantial.
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 two sentences and every clause earns its place: the first lists all validation checks, and the second explicitly routes the agent away from the domain-audit sibling. The information is front-loaded and densely packed without redundancy.
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?
For a single-parameter tool, the description is complete: it states the input, the exact operations, and the key sibling distinction. A minor gap is the absence of return-format information since there is no output schema, but the behavior is specific enough that an agent can infer the nature of the result. Overall, no critical selection or invocation context is missing.
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?
Schema description coverage is 100%, and the single parameter (email) is fully documented in the schema as 'Email address to validate'. The description reinforces that this is a single-address check but adds no new format or constraint details beyond the schema. A baseline score of 3 is appropriate because the schema already carries the parameter semantics.
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 uses a specific verb ('Validate') and clearly identifies the resource ('a single email address'). It then enumerates the exact checks performed (RFC syntax, MX lookup, disposable/role detection), leaving no ambiguity about what the tool does. It also explicitly contrasts itself with email_deliverability_check, making sibling differentiation immediate.
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 explicitly states this is a per-address check and names the alternative for domain-level reputation auditing: 'different from email_deliverability_check, which audits a whole domain's sending reputation...' This gives an agent a clear rule for selecting this tool instead of a sibling. The guidance is explicit enough to avoid misuse.
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.
Many tools audit overlapping site signals (seo_audit vs structured_data_extract vs tech_stack_fingerprint; page_performance_check vs pagespeed_insights; ssl_cert_check vs ssl_labs_grade; broken_link_check vs sitemap_url_validator), so an agent could initially pick the wrong one. Descriptions usually clarify the distinction, but the boundaries are not always obvious.
Most names follow a snake_case target+operation pattern (ssl_cert_check, email_deliverability_check), but check_open_ports and check_robots_sitemap reverse the order, and the action suffixes vary widely (check, audit, validate, lookup, extract, grade, report, insights). Still readable, but not a single predictable convention.
At 29 tools, the server is above the 25-tool threshold and feels like an undifferentiated grab bag of single-purpose audits rather than a tightly scoped toolkit. Many checks could be consolidated (e.g. the separate SSL and performance tools, or domain_report versus its component checks).
For a web/domain/email/security diagnostics toolbelt, the coverage is unusually broad: DNS, TLS, email, SEO, structured data, vulnerabilities, ports, redirects, and more are all represented. Minor gaps exist (no generic HTTP request/debug tool, no zone-transfer or full WHOIS history), but agents can accomplish most diagnostic workflows without hitting dead ends.