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email_spoofability_score

Calculate a domain's email spoofability score from SPF, DKIM, and DMARC records to assess how easily it can be spoofed.

Instructions

Calculate an email spoofability score (0-100) for a domain based on SPF, DKIM, and DMARC configuration. Returns a score, verdict (easily spoofable / moderately protected / well protected), and per-check breakdown.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesThe domain to calculate spoofability score for (e.g. example.com)
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses the output (score, verdict, per-check breakdown) but does not mention whether the tool performs live DNS lookups, whether it is read-only, or any potential side effects. For a 'calculate' tool, the output description adds some transparency, but key behavioral traits are unaddressed.

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 a single, front-loaded sentence that efficiently states the purpose, output format, and scope. Every word contributes value, with no redundancy or filler.

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?

Given the tool's simplicity (one parameter, no output schema), the description adequately covers the return values and scoring basis. The 'per-check breakdown' is slightly vague, but the SPF/DKIM/DMARC context makes it understandable. It is nearly complete for an agent to invoke and interpret the tool.

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?

The schema already provides 100% coverage for the single 'domain' parameter, including an example. The description merely repeats 'for a domain' but adds no new semantic detail beyond the schema. Baseline of 3 applies because the schema does the heavy lifting.

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 'Calculate an email spoofability score (0-100) for a domain based on SPF, DKIM, and DMARC configuration.' This is a specific verb plus resource and scope, and it clearly distinguishes from sibling tools like email_check_spf, email_check_dkim, email_check_dmarc, which focus on individual record checks rather than a composite score.

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

Usage Guidelines3/5

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

The description implies usage—when a composite spoofability score is needed—but does not explicitly state when to prefer this tool over alternatives or when not to use it. No exclusions or alternative tool mentions are provided, so the guidance is only implicit.

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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