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Cyber Risk Signal

cyber_risk
Read-onlyIdempotent

DNS-hygiene + tech-stack-exposure surface for a domain. Returns a 0-100 cyber score (higher = lower risk) with six sub-scores (email security, DNS hardening, domain hygiene, infra exposure, tech-stack exposure, spoofability), critical flags, and concrete recommended actions. Tuned by buyer profile. SCOPE: inspects published DNS only — no port scans, breach lookups, or CVE matching.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesCompany domain, e.g. example.com.
buyer_profileNocyber_insurance_underwriting

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already convey readOnly, idempotent, and non-destructive behavior. The description adds meaningful behavioral context beyond those annotations: the score scale semantics ('higher = lower risk'), the exact components returned, the 'Tuned by buyer profile' behavior, and the hard scope limitation to published DNS with explicit non-actions. This is valuable and consistent with the 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?

The description is three sentences, front-loads the core purpose in the first sentence, and packs output details, score interpretation, and scope constraints into a compact structure. Every sentence adds distinct value with no repetition or filler.

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?

Even though there is no output schema, the description fully characterizes what the caller should expect: a 0-100 score with directionality, six named sub-scores, critical flags, recommended actions, and buyer-profile tuning. It also states the operational scope and exclusions, giving an agent enough context to invoke the tool correctly.

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 50%: 'domain' has a description but 'buyer_profile' does not. The description adds that the result is 'Tuned by buyer profile,' which gives the parameter purpose beyond the schema enum/default. However, it does not explain how different buyer_profile values affect the score or which profiles exist, leaving the undocumented parameter only partially clarified.

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 identifies the tool as assessing a 'DNS-hygiene + tech-stack-exposure surface' for a domain and explicitly states the output: a 0-100 cyber score, six sub-scores, critical flags, and recommended actions. This distinguishes it from sibling DNS tools like dns_lookup or dns_profile by emphasizing the risk-signal output rather than raw DNS records.

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 provides clear context on what the tool covers and explicitly states exclusions: 'inspects published DNS only — no port scans, breach lookups, or CVE matching.' It also notes the score is 'Tuned by buyer profile,' indicating when parameter customization matters. However, it does not name specific sibling tools or state explicit when-to-use versus alternatives.

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

B3.2/5.0
Disambiguation2/5

Multiple tools have genuinely blurry boundaries: company_change vs company_changes differ only by singular/plural yet serve different purposes, company_domain vs company_classify vs company_lookup_auto all accept a domain, geo_zip_lookup vs geo_enrich vs geo_zip_batch all return ZIP profiles, and email_validate subsumes much of email_disposable and email_free_provider. The domain prefixes help narrow search space, but within many domains an agent cannot reliably predict which tool is the right one.

Naming Consistency4/5

All 129 tools uniformly follow a snake_case [domain]_[topic] convention (company_, fx_, geo_, dns_, weather_, tax_), which is highly predictable and consistent. Minor deviations include the confusing company_change/company_changes pair, and inconsistent suffix usage (_batch appears on address_validate_batch, company_domains_batch, geo_zip_batch but not on equivalent lookup tools elsewhere).

Tool Count1/5

129 tools far exceeds the 50+ extreem-mismatch threshold, bundling roughly 28 unrelated data domains (weather, fx, tax, ccompany, dns, jobs, flight, email, phone, tax...) into a single MCP surface. Even focusing on one domain forces the agent to load an enormous unrelated tool list; this should be split into many smaller domain-specific servers.

Completeness4/5

Per-domain coverage is impressively thorough: weather spans current/forecast/hourly/historical/normals/marine/route/air-quality, fx covers rates/convert/historical/volatility/correlation/strenth, and company includes lookup/enrichment/networks/timeline/peer-comparison plus six buyer-tuned signals with profile-introspection tools. Minor gaps like flight being historical-only and smtp probes skipping major email providers are documented scope decisions rather than dead ends.

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