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Email Disposable

email_disposable
Read-onlyIdempotent

Check if email address uses a known disposable/temporary provider (Guerrilla Mail, Temp Mail, Mailinator, etc.). Use for input validation to detect throwaway signups; for domain reputation use threat_intel. Companion email-investigation tools: email_mx (deliverability + MX trust), domain_report on the email's domain (full recon), threat_intel (malware-distribution signal on the domain). Free: 30/hr, Pro: 500/hr. Returns {disposable, domain, provider}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailYesFull email address to check (e.g. 'user@tempmail.com', 'test@guerrillamail.com')

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds behavioral context such as rate limits (Free: 30/hr, Pro: 500/hr) and the return shape ({disposable, domain, provider}), which goes beyond the annotations. No contradictions.

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

Conciseness4/5

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

The description is well-structured and front-loaded with the core purpose, followed by usage guidance, companions, rate limits, and return format. Slightly long but every sentence adds value, and no fluff is present.

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?

The description is complete for an agent to select and invoke: it explains what the tool does, when to use it (and when not), provides alternatives, mentions rate limits, and states the return fields. The input schema fully covers the parameter, and the output schema is mentioned even though it exists.

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% with parameter descriptions and examples. The tool description does not add additional parameter semantics beyond the schema, but the schema already fully covers the 'email' parameter, so baseline 3 is appropriate.

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 states the tool's function: 'Check if email address uses a known disposable/temporary provider' with specific examples. It also distinguishes itself from related tools like threat_intel and email_mx, making it easy to select.

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?

Explicit usage guidance is provided: 'Use for input validation to detect throwaway signups; for domain reputation use threat_intel.' It also names companion tools with their specific purposes, giving clear when-to-use and when-not-to-use context.

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

A4.5/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, with differences between lookup/search/scan/audit for each domain. However, some overlap exists (e.g., email_mx vs email_security_posture, scan_headers vs contrast_scan) which could cause occasional confusion. Overall, boundaries are well-defined.

Naming Consistency5/5

Tool names follow a consistent verb_noun pattern (e.g., cve_lookup, check_headers, bulk_cve_lookup) with all lowercase underscores. Variations like kev_detail or ssl_check are minor and still predictable. No chaotic mixing of conventions.

Tool Count4/5

54 tools is high but justified by the broad cybersecurity scope (CVE, ATLAS, D3FEND, Sigma, domain, email, IOC, scanning). Some redundancy exists (e.g., three email-related tools), but the count is not excessive given the API's comprehensive feature set.

Completeness5/5

The tool set thoroughly covers the threat intelligence and domain investigation lifecycle: CVE/KEV/exploit/CWE, ATLAS/D3FEND/Sigma, DNS/WHOIS/SSL/subdomains, email security, IOC enrichment, and active scanning. No significant gaps are apparent for the stated cybersecurity purpose.