smithery/neversight

open-meteo

Integrate Open-Meteo Weather Forecast, Air Quality, and Geocoding APIs: query design, variable selection, timezone/timeformat/units, multi-location batching, and robust error handling.

Installation

$ npx skills add smithery/neversight --skill open-meteo

Summary

  • Integrate Open-Meteo Weather Forecast, Air Quality, and Geocoding APIs: query design, variable selection, timezone/timeformat/units, multi-location batching, and robust error handling.
  • Keywords: Open-Meteo, /v1/forecast, /v1/air-quality, geocoding-api, hourly, daily, current, timezone=auto, timeformat=unixtime, models, WMO weather_code, CAMS, GeoNames, httpx, FastAPI, pytest.

Similar popular skills

Related neighbors and high-traction skills in the same topics — useful to compare before installing.

Also in this package

Other skills from smithery/neversight · top by installs.

npx skills add smithery/neversight

Browse all from smithery/neversight

More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Skill metadata

Parsed from SKILL.md frontmatter.

Version1.4.17

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 5,397 B
  • docs SUMMARY.md 396 B

History

  1. First recorded snapshot · 0 installs

SKILL.md

Open Meteo

When to use

  • You need weather forecasts (hourly/daily/current) for coordinates.
  • You need air quality / pollen forecasts (hourly/current) for coordinates.
  • You need to resolve a user-provided place name to coordinates and timezone (geocoding).
  • You need to support multi-location batching (comma-separated lat/lon lists).
  • You need a deterministic checklist for Open-Meteo query parameters, response parsing, and error handling.

Goal

Provide a reliable, production-friendly way to call Open-Meteo APIs (Forecast, Air Quality, Geocoding), choose variables, control time/units/timezone, and parse responses consistently.

Steps

  1. Pick the correct API and base URL

- Forecast: https://api.open-meteo.com/v1/forecast - Air Quality: https://air-quality-api.open-meteo.com/v1/air-quality - Geocoding: https://geocoding-api.open-meteo.com/v1/search

  1. Resolve coordinates (if you only have a name)

- Call Geocoding with name and optional language, countryCode, count. - Use the returned latitude, longitude, and timezone for subsequent calls.

  1. Design your time axis (timezone, timeformat, and range)

- Prefer timezone=auto when results must align to local midnight. - If you request daily=..., set timezone (docs: daily requires timezone). - Choose timeformat=iso8601 for readability, or timeformat=unixtime for compactness. - If using unixtime, remember timestamps are GMT+0 and you must apply utcoffsetseconds for correct local dates. - Choose range controls: - forecastdays and optional pastdays, or - explicit startdate/enddate (YYYY-MM-DD), and for sub-daily starthour/endhour.

  1. Choose variables minimally (avoid "download everything")

- Forecast: request only the variables you need via hourly=..., daily=..., current=.... - Air Quality: request only the variables you need via hourly=..., current=.... - Keep variable names exact; typos return a JSON error with error: true.

  1. Choose units and model selection deliberately

- Forecast units: - temperatureunit (celsius / fahrenheit) - windspeedunit (kmh / ms / mph / kn) - precipitationunit (mm / inch) - Forecast model selection: - default models=auto / “Best match” combines the best models. - you can explicitly request models via models=.... - provider-specific forecast endpoints also exist (provider implied by path). See references/models.md (section "Endpoints vs models=") for examples and doc links. - for provider/model-specific selection tradeoffs, see references/models.md. - Air Quality domain selection: - domains=auto (default) or camseurope / camsglobal.

  1. Implement robust request/response handling

- Treat HTTP errors and JSON-level errors separately. - JSON error format is: - {"error": true, "reason": "..."} - When requesting multiple locations (comma-separated coordinates), expect the JSON output shape to change to a list of structures. - Optionally use format=csv or format=xlsx when you need data export.

  1. Validate correctness with a “known city” check

- Geocode “Berlin” → Forecast hourly=temperature2m for 1–2 days → verify timezone and array lengths. - Air Quality hourly=pm10,pm25,europeanaqi → verify units and presence of hourlyunits.

Critical prohibitions

  • Do not include out-of-scope APIs in this skill’s implementation guidance: Historical Weather, Ensemble Models, Seasonal Forecast, Climate Change, Marine, Satellite Radiation, Elevation, Flood.
  • Do not omit timezone when requesting daily variables (per docs).
  • Do not assume unixtime timestamps are local time; they are GMT+0 and require utcoffsetseconds adjustment.
  • Do not silently ignore {"error": true} responses; fail fast with the provided reason.
  • Do not request huge variable sets by default; keep queries minimal to reduce payload and avoid accidental overuse.

Definition of done

  • You can geocode a place name and obtain coordinates/timezone.
  • You can fetch Forecast data with at least one hourly, one daily (with timezone), and one current variable.
  • You can fetch Air Quality data for at least one pollutant and one AQI metric.
  • Your client code handles both HTTP-level failures and JSON-level error: true with clear messages.
  • Attribution requirements from the docs are captured for Air Quality (CAMS) and Geocoding (GeoNames).

Links

  • Official docs (in-scope):

- https://open-meteo.com/en/docs - https://open-meteo.com/en/docs/air-quality-api - https://open-meteo.com/en/docs/geocoding-api

  • Skill references:

- references/forecast-api.md - references/models.md - references/weather-codes.md - references/air-quality-api.md - references/geocoding-api.md - references/examples.md