Agent-Skills.md

Agent Skills: 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. 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.

UncategorizedID: itechmeat/llm-code/open-meteo

Repository

itechmeat/llm-code
itechmeatLicense: MIT
2

Install this agent skill to your local

pnpm dlx add-skill https://github.com/itechmeat/llm-code/tree/HEAD/skills/open-meteo

Skill Files

Browse the full folder contents for open-meteo.

Download Skill

Loading file tree…

skills/open-meteo/SKILL.md

Skill Metadata

Name
open-meteo
Description
"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."

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

  2. 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.

  3. 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 utc_offset_seconds for correct local dates.
    • Choose range controls:
      • forecast_days and optional past_days, or
      • explicit start_date/end_date (YYYY-MM-DD), and for sub-daily start_hour/end_hour.

  4. 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.

  5. Choose units and model selection deliberately

    • Forecast units:
      • temperature_unit (celsius / fahrenheit)
      • wind_speed_unit (kmh / ms / mph / kn)
      • precipitation_unit (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 cams_europe / cams_global.

  6. 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.

  7. Validate correctness with a “known city” check

    • Geocode “Berlin” → Forecast hourly=temperature_2m for 1–2 days → verify timezone and array lengths.
    • Air Quality hourly=pm10,pm2_5,european_aqi → verify units and presence of hourly_units.

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 utc_offset_seconds 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