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assess_spoofability

Read-onlyIdempotent

Compute a composite email spoofability risk score (0–100, higher = more spoofable) by combining SPF trust surface, DMARC enforcement, and DKIM coverage. Returns a risk level (minimal→critical), per-control sub-scores, and plain-language summary of how easy it would be to spoof email from the domain. Use when asked how easy it is to spoof email from a domain, or for a composite email spoofing risk score.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesDomain to check (e.g., example.com)
formatNoOutput verbosity. Auto-detected if omitted.
force_refreshNoBypass cache and run a fresh check. Useful after DNS changes.

TDQS

A4.2/5.0
Behavior4/5

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

With annotations already declaring readOnlyHint=true, idempotentHint=true, and destructiveHint=false, the description adds value by explaining how the score is computed (combining SPF trust surface, DMARC enforcement, DKIM coverage) and what outputs to expect (risk level, sub-scores, plain-language summary). This goes beyond annotation coverage and helps 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?

Two sentences, no repetition of schema content, and the most important information (what the tool does and its output) is front-loaded. Every phrase serves a purpose, with the usage note placed last as a natural call to action.

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?

The tool has no output schema, so the description's explanation of returned data (risk level, sub-scores, summary) is valuable. It covers the core behavior and usage context. Minor gaps like handling of invalid domains or network-only data sources exist, but they are not critical for a read-only, idempotent 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?

Schema description coverage is 100%, so the baseline is 3. The description doesn't add parameter-level details beyond what the schema already provides (domain, format, force_refresh). It doesn't harm, but it also doesn't compensate further.

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 starts with a specific verb ('Compute') and clearly names the resource ('composite email spoofability risk score'), including the 0–100 scale and direction. It explicitly distinguishes itself from sibling tools like check_spf, check_dmarc, and check_dkim by framing this as a combined/composite assessment rather than a single-control check.

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 gives explicit usage triggers: 'Use when asked how easy it is to spoof email from a domain, or for a composite email spoofing risk score.' It implies alternatives (individual control checks) exist among siblings but does not name them or state when NOT to use this tool. This is clear context but lacks exclusions.

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

A3.6/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, with detailed descriptions that help differentiate overlapping areas (e.g., check_dane vs check_dane_https). However, there are sets of similar tools (brand audit, OSINT, polling) that could cause confusion if descriptions are not carefully read.

Naming Consistency3/5

The naming is mostly readable but inconsistent: many check_* tools follow a verb_noun pattern, but there are also noun_verb names (scan_domain, cymru_asn), bare verbs (generate), and varied patterns for async operations (discover_brand_domains_start vs discover_brand_domains).

Tool Count2/5

With 80 tools, the server feels overstuffed. It covers multiple domains (DNS, email, brand, OSINT, M365) that could benefit from separation. The high number includes many polling/status tools that add overhead.

Completeness3/5

The server covers core DNS and email security checks thoroughly, including many edge cases (e.g., BIMI, MTA-STS, subdomain takeover). However, there are gaps like lack of direct DNS record management and some OSINT tools are restricted to operator deployment, leaving agents with dead ends.