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ScamVerify

check_email

Read-onlyIdempotent

Analyze emails for phishing threats by checking sender domains, email headers (SPF/DKIM/DMARC), brand impersonation, embedded URLs, and phone numbers to identify potential scams.

Instructions

Analyze an email for phishing indicators. Checks sender domain, email headers (SPF/DKIM/DMARC), brand impersonation, embedded URLs and phone numbers. Returns unified risk score with detailed header and sender analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
email_bodyYesEmail body content to analyze (max 20000 characters)
sender_emailNoSender email address
subjectNoEmail subject line
raw_headersNoRaw email headers for SPF/DKIM/DMARC analysis

Implementation Reference

  • The `check_email` tool registration and handler implementation. It analyzes email content, sender, subject, and headers using the `/api/v1/email/analyze` endpoint.
    server.tool(
      'check_email',
      'Analyze an email for phishing indicators. Checks sender domain, email headers (SPF/DKIM/DMARC), brand impersonation, embedded URLs and phone numbers. Returns unified risk score with detailed header and sender analysis.',
      {
        email_body: z.string().describe('Email body content to analyze (max 20000 characters)'),
        sender_email: z.string().optional().describe('Sender email address'),
        subject: z.string().optional().describe('Email subject line'),
        raw_headers: z.string().optional().describe('Raw email headers for SPF/DKIM/DMARC analysis'),
      },
      {
        title: 'Analyze Email',
        readOnlyHint: true,
        destructiveHint: false,
        idempotentHint: true,
        openWorldHint: true,
      },
      async ({ email_body, sender_email, subject, raw_headers }) => {
        try {
          const body: Record<string, unknown> = { email_body };
          if (sender_email) body.sender_email = sender_email;
          if (subject) body.subject = subject;
          if (raw_headers) body.raw_headers = raw_headers;
          const data = await apiPost('/api/v1/email/analyze', body);
          return jsonResult(data);
        } catch (err) {
          return errorResult(err instanceof Error ? err.message : 'Email analysis failed');
        }
      },
    );
Behavior4/5

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

Supplements annotations (readOnly/idempotent) by detailing specific security checks performed (brand impersonation, header authentication) and disclosing return format ('unified risk score'). Does not contradict annotations. Minor gap: doesn't elaborate on openWorldHint implications.

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?

Two efficiently structured sentences: first establishes purpose and analysis scope, second describes return value. No filler content; every clause adds actionable information about capabilities or outputs.

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

Completeness4/5

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

Strong coverage for a 4-parameter security tool. Compensates for missing output schema by describing return value ('unified risk score with detailed analysis'). Annotations cover safety profile. Minor gap: doesn't explicitly note that only email_body is required, though schema indicates this.

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?

With 100% schema coverage, baseline is 3. Description adds value by mapping parameters to specific analysis functions: raw_headers used for 'SPF/DKIM/DMARC' checks, sender_email used for 'sender domain' verification, email_body scanned for 'embedded URLs and phone numbers.'

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?

Description opens with specific verb 'Analyze' and resource 'email', clearly targeting phishing indicators. Distinguishes from siblings (check_url, check_phone) by mentioning email-specific elements like SPF/DKIM/DMARC headers, sender domain, and 'embedded' URLs/phone numbers.

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?

Provides clear context that this is for email analysis, and by noting it checks 'embedded URLs and phone numbers' implicitly distinguishes from standalone check_url/check_phone tools. However, lacks explicit 'when not to use' guidance or direct sibling comparisons.

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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