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UPinar

contrastapi

by UPinar
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

email_mx

Read-onlyIdempotent

Analyze email security configuration for a domain: check MX records, SPF, DMARC, DKIM, mail provider, and security grade. Verify email authentication setup and assess phishing risk.

Instructions

Analyze email security: MX records, SPF policy, DMARC policy, DKIM probe across common+date-based selectors, mail provider, grade. Use to verify email-auth setup and phishing risk; for full audit use domain_report. Free: 100/hr, Pro: 1000/hr. email_security.dkim_status reports honest evidence: 'verified' iff at least one selector responded, else 'unverifiable' (custom selectors cannot be discovered without prior knowledge). Grade: when DKIM verified, A=SPF+DMARC+DKIM/B=2of3/C=1of3; when DKIM unverifiable, A=SPF+DMARC/B=one/F=neither — DKIM absence is NOT penalized because it is unprovable in DNS. Returns {mx_records, mail_provider, email_security:{spf, dmarc, dkim_selectors, dkim_status, grade, issues}, summary}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesDomain to analyze email configuration for (e.g. 'example.com', 'google.com')

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Tool Definition Quality

A4.7/5.0
Behavior5/5

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

Adds extensive detail beyond annotations: how DKIM verification works, grading logic when DKIM unverifiable, and the meaning of dkim_status. No contradiction with annotations.

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?

Concise yet comprehensive; every sentence adds value. Well structured with clear explanations.

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?

Complete given one parameter, rich annotations, and stated return fields. Covers usage, behavior, and output expectations.

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 coverage is 100%, and the description provides context on domain usage. Baseline 3 is appropriate as no additional parameter details are needed.

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?

Clearly states the tool analyzes email security (MX, SPF, DMARC, DKIM, mail provider, grade) and distinguishes from domain_report for full audit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says use for verifying email-auth setup and phishing risk, and directs to domain_report for full audit. Also includes rate limits.

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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