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weather_aviation_iah

IAH weather delay risk for the next 48 hours. Weather-driven delay risk for Houston Bush (IAH) over the next 48 hours: 6-hour risk scores from forecast wind gusts, convective potential, winter and sustained precipitation, and heavy cloud cover at the field. Same shape as the generic delay-risk endpoint, bound to IAH. [HTTP: GET /v1/aviation/delay-risk/IAH · price $0.02 via x402 · docs https://x402-factory.com/docs/weather.aviation.iah]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden, and it does disclose useful behavior: 6-hour risk buckets, a 48-hour horizon, and the underlying drivers (wind gusts, convective potential, winter and sustained precipitation, heavy cloud cover). It also surfaces a real operational constraint not in any structured field — the $0.02 x402 price and the HTTP endpoint. It stops short of describing output fields or failure modes, hence not a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The lead sentence is well front-loaded, but the second sentence largely restates it ('Weather-driven delay risk for Houston Bush (IAH) over the next 48 hours'), which is redundant. The bracketed HTTP/price/docs block is dense metadata appended to the tail rather than integrated, so the text is longer than it needs to be.

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 annotations, no output schema, and no parameters, the description adequately covers what the tool computes, over what horizon and granularity, and what it costs. The only gap is that the actual return shape is deferred to 'same shape as the generic delay-risk endpoint' rather than described, which is a minor omission for a fixed-shape read endpoint.

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?

The tool takes zero parameters (empty schema, additionalProperties false), so there is nothing to disambiguate; the baseline for a parameterless tool is 4. The description's time horizon (48h) and 6-hour granularity implicitly characterize what comes back rather than any input semantics.

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?

States a specific resource (weather-driven delay risk for Houston Bush/IAH) with a clear scope (next 48 hours) and a specific verb context (risk scoring). The sibling set contains many airport-bound and generic delay-risk tools, and the description names the distinction ('bound to IAH', 'same shape as the generic delay-risk endpoint'), so an agent can route without opening a schema.

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 phrase 'bound to IAH' and the reference to the generic delay-risk endpoint imply when to pick this variant, but there is no explicit when-to-use/when-not guidance or a named alternative (e.g., 'use weather_aviation-delay-risk for all airports, or weather_aviation_dfw for Dallas'). Usage is inferred rather than stated.

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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