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mariow

aviation-weather-mcp

by mariow

wx_outlook

Forecast VFR confidence 3-15 days ahead for any airfield, reporting daily probability of poor conditions (low cloud or thunderstorms) to plan trips beyond short-range TAFs.

Instructions

Longer-range VFR confidence outlook (3–15 days) for an airfield or location. Pools an ensemble (ECMWF-ENS for low cloud; ECMWF-ENS + GEFS for CAPE) and reports, per day, the probability that the day is NO-GO — the share of ensemble members with poor VFR conditions (low cloud above threshold OR high CAPE/thunderstorm potential) during the daylight window. Also shows the deterministic ECMWF-IFS trend, plus the ICON-EU run (≤5 days) as an independent medium-range cross-check that sits between ICON-D2 (48h) and ECMWF (15d). This is the confidence measure for trip planning that short-range METAR/TAF/ICON-D2 cannot provide. Pass an ICAO code (resolved offline from a bundled airport database covering GA fields) or lat/lon directly.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNoLatitude in decimal degrees (alternative to icao)
lonNoLongitude in decimal degrees (alternative to icao)
daysNoForecast horizon in days, 3–15 (default: 7)
icaoNo4-letter ICAO airport code (preferred; coords resolved from the station DB). Provide this OR lat+lon.
end_hourNoDaylight window end, local hour 1–24 (default: 18)
start_hourNoDaylight window start, local hour 0–23 (default: 8)
cape_thresholdNoCAPE J/kg that counts as No-Go / thunderstorm potential (default: 1000)
cloud_thresholdNoLow-cloud cover % that counts as No-Go (default: 50)
Behavior4/5

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

With no annotations, the description transparently explains the ensemble models, the NO-GO probability definition, thresholds, and the ICON-EU cross-check. It does not detail output formatting or error behavior, but the operational mechanics are well disclosed for a read-only forecast tool.

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?

Though dense, the description front-loads the core purpose and every sentence contributes unique operational detail—models, probability metric, cross-check logic, and input modes. It is appropriately sized for the tool's complexity with no filler.

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

Completeness5/5

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

For a multi-model tool with 8 parameters, no output schema, and no annotations, the description fully covers purpose, inputs, methodology, and relation to siblings. It sufficiently describes what is reported (probability, deterministic trend, cross-check) for an agent to invoke correctly.

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

Parameters5/5

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

Schema descriptions already cover 100% of parameters, and the description adds valuable semantics: what counts as NO-GO, how thresholds are interpreted, the daylight-window concept, and the offline airport database for ICAO resolution. This goes well beyond standard field names.

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 names a specific resource and action: 'Longer-range VFR confidence outlook (3–15 days)' and contrasts it with short-range METAR/TAF/ICON-D2. This clearly distinguishes it from siblings and leaves no ambiguity about its function.

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

Usage Guidelines5/5

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

It explicitly positions the tool as the confidence measure for trip planning that short-range siblings cannot provide, naming METAR/TAF/ICON-D2. It also specifies input alternatives (ICAO or lat/lon) and the 3–15 day horizon, giving clear when-to-use 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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