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Site Risk Snapshot

site_risk
Read-onlyIdempotent

Physical-location risk composite for a US ZIP. Joins FEMA flood + USGS seismic + NOAA tornado/hurricane + climate + EIA grid reliability into a 0-100 risk-weighted score (higher = lower risk). Tuned by site profile: insurance_underwriting, data_center_site, retail_storefront, warehouse_distribution. Returns underwriting_hint mapped to insurance actions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
zipYes
site_profileNoinsurance_underwriting

TDQS

A4.4/5.0
Behavior4/5

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

The annotations already establish read-only, idempotent, and non-destructive behavior, and the description does not contradict them. It adds useful behavioral context by disclosing that the score is a weighted composite of named government/climate/grid datasets and that a higher score means LOWER risk, which is non-obvious.

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 compact and front-loaded: the core purpose is in the first sentence, and each following sentence adds a distinct piece of value—data sources, scoring interpretation, profile tuning, and output. No filler or repetition exists.

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?

With no output schema, the description compensates by stating the 0-100 score, the risk direction, the dependence on site_profile, and the underwriting_hint return. It leaves minor gaps around exact response shape and zip input format, but for a two-parameter read-only composite, the coverage is strong.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must carry parameter meaning. It does: 'US ZIP' clarifies the zip field, and the site_profile enum values are repeated with the explanation that they tune the risk weighting. It could add zip format details or profile effect specifics, but both parameters are meaningfully addressed.

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 opens by naming the resource and subject exactly: 'Physical-location risk composite for a US ZIP.' It then specifies the data sources, score range, profile tunings, and the underwriting_hint output, making its purpose unmistakable and distinguishing it from sibling geo/weather/address lookups.

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 clear usage context by listing the four site profiles and noting that the result includes an underwriting_hint, implying underwriting and site-selection use cases. However, it does not explicitly name alternative tools or state when this tool should not be used, so it stops short of full routing 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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