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Domain Comparison (Phishing/Typosquat Detection)

dns_compare
Read-onlyIdempotent

Compare a target domain against a reference for phishing / typosquatting / lookalike detection. Computes edit distance, apex/TLD diff, homoglyph substitution detection (0↔o, 1↔l, rn↔m). Flags is_likely_typosquat + is_likely_lookalike with drivers. Pure analytical comparison — no DNS query.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetYesSuspect domain, e.g. striipe.com.
referenceYesKnown-good domain, e.g. stripe.com.

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already signal readOnly/idempotent/non-destructive, and the description adds valuable behavioral specifics: the computation includes edit distance, apex/TLD diff, and homoglyph substitution with concrete substitutions, and the result flags are is_likely_typosquat and is_likely_lookalike with drivers. Stating 'no DNS query' clarifies there are no network side effects, which is beyond annotation semantics.

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?

Three sentences deliver the purpose, the algorithmic internals, and the key caveat without filler. The most selection-relevant information (compare, no DNS query) is front-loaded.

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 there is no output schema, the description usefully names the output flags and drivers, plus the computed dimensions. It doesn't fully specify the response shape or define 'drivers,' but for tool selection and invocation the inputs, outputs, and side-effect boundary are sufficiently covered.

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 documents both parameters with descriptions and examples (target: 'Suspect domain, e.g. striipe.com'; reference: 'Known-good domain, e.g. stripe.com'), and description coverage is 100%. The description merely mirrors this relationship rather than adding new constraints, formats, or default behavior.

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 names a specific action ('Compare a target domain against a reference') and a concrete detection purpose (phishing/typosquatting/lookalike). It distinguishes dns_compare from the many dns_* siblings by closing with 'Pure analytical comparison — no DNS query,' so an agent can select it without opening schemas.

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?

Explicitly frames this as pure analytical comparison and rules out DNS querying, which prevents confusion with dns_lookup/dns_history/dns_profile. It neither lists alternatives by name nor gives a when-not-to-use rule (e.g., 'for resolution use dns_lookup'), but the exclusion plus sibling context supplies adequate guidance.

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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