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weather_forecast-window_washington-dc

Will it rain in Washington, DC during your event window. Event-window weather odds for Washington, DC: pass a start and end time (or omit them for the next six hours) and get rain probability and expected conditions across the window — built for scheduling decisions. Same shape as /v1/forecast/window with the Washington, DC coordinates built in. [HTTP: GET /v1/forecast/washington-dc/window · price $0.02 via x402 · docs https://x402-factory.com/docs/weather.forecast-window.washington-dc]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNoWindow end (ISO-8601), ≤12h after start. Default: start + 6h.
startNoWindow start (ISO-8601). Default: the top of the next hour.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does real work: it discloses the default window (next six hours when params are omitted), the elements returned (rain probability and expected conditions), and the payment regime (price $0.02 via x402, HTTP GET). It does not cover failure/limit behavior such as how far ahead start may be requested, so it stops short of full disclosure.

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

Conciseness4/5

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

The key question ('Will it rain ... during your event window') and the default behavior are front-loaded, and the sibling-relationship note follows usefully. The bracketed metadata footer (endpoint, price, docs URL) is dense but adds operational value rather than pure filler.

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?

There is no output schema, and the description compensates by naming the returned signals (rain probability, expected conditions) plus the default window and cost. For a zero-required-param tool this is nearly sufficient; only the permitted forecast horizon for a future start is left unaddressed.

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 description coverage is 100%, so both parameters already document their ISO-8601 format and defaults. The description restates the omit-them-for-six-hours default but adds no syntax or constraint detail beyond the schema, so the baseline of 3 applies.

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 verb and resource ('Will it rain in Washington, DC during your event window ... get rain probability and expected conditions across the window') and differentiates itself from the generic sibling by noting it is 'the same shape as /v1/forecast/window with the Washington, DC coordinates built in.' An agent can separate it from weather_forecast_washington-dc and weather_forecast-window without opening any schema.

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?

Gives clear triggering context ('built for scheduling decisions', pass start/end or omit them for the next six hours), which tells the agent when this window tool applies. It does not explicitly name the sibling to prefer for a single-point current forecast, so the routing guidance is implicit rather than stated as an exclusion.

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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