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email_domain_health_check

Read-onlyIdempotent

Comprehensive email domain health check: MX routing, SPF authentication, DKIM signing, DMARC policy enforcement, DNSBL blacklist status (Spamhaus/SpamCop/Barracuda), TLS certificate validity, and WHOIS registration age. Aggregates a reputation score 0-100 and generates P0/P1/P2 deliverability signals. Accepts a domain (stripe.com) or email address (info@stripe.com). Detects role-based addresses (info@, support@, admin@, noreply@) that have higher bounce rates. Detects email provider (Google Workspace, Microsoft 365, Amazon SES, etc.). P0 signals: blacklisted / no MX / TLS expired / no SPF + DMARC none. P1 signals: SPF soft-fail / no DKIM selector / DMARC no reporting. P2 signals: role-based address / TLS expires <30d / domain age <90 days. All checks are keyless (no API keys required). Cache TTL 1h. SLA <=10s p95.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asyncNoIf true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts.
emailNoFull email address for additional checks: format validity, role-based detection (e.g. "ceo@stripe.com").
checksNoSubset of checks to run. Defaults to all 8: ["mx","spf","dkim","dmarc","blacklist","whois","tls","reputation"]. Use a subset for faster responses (e.g. ["mx","spf","dmarc","reputation"] for quick scoring).
domainYesDomain to check (e.g. "stripe.com" or "@stripe.com"). If an email address is provided here, the domain is extracted automatically.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
mxYes
spfYes
tlsNo
dkimYes
dmarcYes
whoisNo
domainYes
statusYes
sourcesYes
blacklistYes
email_validNo
quality_scoreYes
reputation_scoreYes
email_is_role_basedNo
deliverability_signalsYes

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already indicate read-only, non-destructive, idempotent behavior. The description adds valuable transitive details: keyless operation, 1-hour cache TTL, sub-10-second p95 SLA, and the generation of a 0-100 reputation score with P0/P1/P2 signal tiers. These specifics go beyond annotations and help set expectations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense yet well-organized: it starts with the core purpose, then lists checks, then discusses input flexibility and signal levels, and finally operational constraints. Every sentence carries distinct information, and the length is appropriate for the tool's complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity and the presence of an output schema (which explains return values), the description is complete: it covers inputs, specific checks, output signals, performance characteristics, and constraints. No crucial usage aspect is missing.

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?

Schema descriptions cover all parameters (domain, email, checks, async) at 100%. The description augments the 'checks' parameter by explaining the meaning of check types via P0/P1/P2 signal examples, and also clarifies the dual input format (domain or email). This adds value beyond the schema but does not fully explain every nuance (e.g., async semantics are only in 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 identifies the tool as a comprehensive email domain health check, enumerating specific checks (MX, SPF, DKIM, DMARC, DNSBL, TLS, WHOIS) and deliverability signals. This specific verb+resource combination distinguishes it from sibling tools like 'domain_tech_fingerprint' which focus on different aspects.

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 provides clear context for when to use the tool: for email deliverability assessment via domain/email input. It mentions keyless operation and SLA, implying readiness for production use. However, it does not explicitly compare to alternative tools or state exclusions, so it falls short of a 5.

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

C2.4/5.0
Disambiguation1/5

Over 50 tools share the identical template 'Gapup agent-payable C-suite expertise' with similar French descriptions and reference cases, making their boundaries indistinguishable. Clusters like competitor_intel, competitive_deep_dive, competitor_moves, competitor_profiles, competitor_pricing_radar, competitor_pricing_scrape, and competitor_recommendations heavily overlap in purpose.

Naming Consistency1/5

Names are chaotic: mix of French and English, snake_case and camelCase, verb_noun, noun, and adjective forms with no uniform pattern. Examples like 'bp_narratif', 'content_enrichment', 'ai_governance_full_report_async', and 'job_result' show no coherent naming convention.

Tool Count1/5

271 tools is far beyond any reasonable MCP server scope, creating an overwhelming selection burden for agents. This count vastly exceeds the 25+ threshold for 'too many' and makes navigation impractical.

Completeness2/5

While the server covers many business domains, it lacks lifecycle operations (e.g., no update/delete tools for the deliverables it generates) and the input specifications are vague ('documented case fields' without documentation), creating functional dead ends. The sheer breadth does not compensate for these gaps.