windext

Rideable windows

ride_windows

Read-onlyIdempotent

Find rideable daytime wind windows at a spot by checking model consensus stays within your knot range, excluding offshore and forbidden sectors unless allowed.

Instructions

Contiguous daytime windows where the model-consensus wind sits inside the rider's range, excluding offshore wind and the spot's forbidden sectors unless allowed.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "ride_windows"
  }
}

Input Schema

Name	Required	Description
`lat`	No
`lon`	No
`days`	No
`max_kn`	No
`min_kn`	No	Minimum usable wind in knots (kite ~12, wing ~12, windsurf ~14, big kite/foil ~8)
`spot_id`	No	Spot id from find_spot (preferred over raw coordinates: enables orientation and direction knowledge)
`facing_deg`	No
`allow_offshore`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 17, 2026

TDQS

B3.4/5.0

Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so the description earns credit for disclosing domain behavior: multi-model consensus rather than a single forecast, daytime-only restriction, offshore exclusion, and forbidden-sector filtering unless allow_offshore is set. It stops short of describing result shape, timezone handling, or how consensus is computed.

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?

A single front-loaded sentence with no filler; the filtering constraints come in a logical order. It is dense but every clause (consensus, daytime, offshore, forbidden sectors, allowance) conveys a real constraint.

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?

For an 8-parameter, no-required-args, open-world tool with no output schema, the description identifies what a "window" is but not its format, units, timezone, or how many are returned. The parameter coverage gap and absent output schema leave meaningful questions unanswered.

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 coverage is only 25% (min_kn and spot_id documented), so the description must carry weight. It does map conceptually onto several parameters — "rider's range" to min_kn/max_kn, "offshore" to allow_offshore, "forbidden sectors" to facing_deg/spot orientation — but lat, lon, and days receive no clarification in either place.

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?

The description names a concrete computed output — contiguous daytime windows where model-consensus wind falls inside the rider's range — which goes well beyond the tautological title. It implicitly differentiates from spot_forecast (raw forecast) by describing a filtered, derived result, though it never names the sibling.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no statement of when to call this versus spot_forecast, tides, or spot_info, nor any prerequisites or exclusions. The agent must infer usage purely from the output description.

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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