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weather_forecast_detroit

Hourly Detroit weather forecast (blend model, method labeled). Hourly weather forecast for Detroit: temperature, precipitation probability, and wind, up to 168 hours out. NWS-derived series, bias-blended with our calibrated station model where covered — every response labels the method that produced it. Same shape as /v1/forecast/point with the Detroit coordinates built in. [HTTP: GET /v1/forecast/detroit · price dynamic ($0.01 for hours ≤ 48, $0.03 beyond) via x402 · docs https://x402-factory.com/docs/weather.forecast.detroit]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hoursYes
unitsYesimperial

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does reasonably well: it discloses data provenance (NWS-derived, bias-blended with a calibrated station model), that each response labels the producing method, the transport (HTTP GET /v1/forecast/detroit), and a non-trivial pricing model ($0.01 for hours ≤ 48, $0.03 beyond, paid via x402). It omits auth semantics beyond the payment hint and any caching or rate-limit behavior, keeping it out of 5 territory.

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 core information is front-loaded and the bracketed endpoint/pricing/docs block at the end is a compact, useful convention. But the opening two sentences are near-duplicates ('Hourly Detroit weather forecast...' / 'Hourly weather forecast for Detroit: ...'), which wastes space in an otherwise tight ~90-word description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, and the description does cover the return fields (temperature, precipitation probability, wind), which is the right move. But for a 2-parameter paid tool it leaves 'units' completely unaddressed and misstates the hours ceiling relative to the schema, so an agent cannot reliably call it without inspecting the schema.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate, and it largely does not. The 'units' parameter is never mentioned at all, and the stated horizon of 'up to 168 hours out' directly conflicts with the schema's maximum of 240, which is actively misleading rather than merely incomplete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource (hourly Detroit forecast) and enumerates the variables returned (temperature, precipitation probability, wind). It also distinguishes itself from the generic sibling by noting it is 'the same shape as /v1/forecast/point with the Detroit coordinates built in.' The first two sentences restate each other, which dilutes rather than clarifies, so it stops short of a 5.

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 comparison to '/v1/forecast/point with the Detroit coordinates built in' implicitly tells an agent to pick this tool when Detroit is the target and the generic point tool otherwise. However, it never mentions the closely related weather_forecast-window_detroit sibling or when a windowed view would be preferable, and there is no explicit when-not 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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