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Get Started Free →Get current weather and forecasts with zero API keys — wttr.in one-liners for humans, Open-Meteo JSON for data, with the exact curl commands and format codes. Use when asked what's the weather, will it rain today, forecast for a city, or get me weather data for a location. Produces the live conditions or forecast pulled via curl, interpreted plainly, with the source timestamp and the command used shown so the user can rerun it.
.claude/skills/mohitagw15856-weather-now/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 167% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 537% | 0% |
| case-18 | ✗→✓ | ▲ Improved | 152% | 0% |
| case-19 | ✗→✓ | ▲ Improved | 154% | 0% |
| case-20 | ✗→✓ | ▲ Improved | 48% | 0% |
Weather is the perfect agent utility: everyone asks, and two excellent services answer over plain HTTPS with no keys, no signup, no SDK. This skill knows both — wttr.in for beautiful one-line and full-terminal answers, Open-Meteo for structured JSON when the task needs numbers — plus the format codes and fallback discipline that make the answer reliable instead of lucky.
Ask for these if not provided:
curl -s "wttr.in/Tokyo?format=3" → one line. Format codes: %c condition icon, %t temp, %h humidity, %w wind, %p precipitation, %m moon phase — compose as ?format="%l:+%c+%t,+wind+%w". Full 3-day panel: curl -s "wttr.in/Tokyo" (add ?m metric, ?u imperial, ?T no-color for parsing). Airport codes work: wttr.in/nrt. PNG for sharing: wttr.in/Tokyo.png.curl -s "https://api.open-meteo.com/v1/forecast?latitude=35.68&longitude=139.69¤t_weather=true" → JSON. Rich forecasts: append &hourly=temperature_2m,precipitation_probability&daily=temperature_2m_max,temperature_2m_min,precipitation_sum&timezone=auto&forecast_days=3. Geocode names first when needed: https://geocoding-api.open-meteo.com/v1/search?name=Tokyo&count=1.The one-sentence answer to what they actually asked.]
Conditions table or forecast lines, right units]
Source: wttr.in / Open-Meteo] at response timestamp] · rerun: [the exact curl] Live data, advisory only — for safety-critical decisions use official meteorological services.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 25,075 | 22,317 | -11% | 1 | 1 | 0% | 1,534 | 4,099 | +167% | 0 | 0 | — |
case-02 | fail→fail | 14,597 | 16,577 | +14% | 1 | 1 | 0% | 2,024 | 2,783 | +38% | 0 | 0 | — |
case-03 | fail→pass | 8,255 | 13,131 | +59% | 1 | 1 | 0% | 382 | 2,432 | +537% | 0 | 0 | — |
case-04 | fail→fail | 12,450 | 11,233 | -10% | 1 | 1 | 0% | 1,330 | 2,103 | +58% | 0 | 0 | — |
case-05 | pass→pass | 5,408 | 10,564 | +95% | 1 | 1 | 0% | 766 | 1,788 | +133% | 0 | 0 | — |
case-06 | pass→pass | 14,400 | 4,067 | -72% | 1 | 1 | 0% | 1,113 | 1,682 | +51% | 0 | 0 | — |
case-07 | pass→pass | 11,567 | 9,667 | -16% | 1 | 1 | 0% | 1,069 | 1,824 | +71% | 0 | 0 | — |
case-08 | pass→pass | 11,793 | 13,917 | +18% | 1 | 1 | 0% | 1,432 | 2,400 | +68% | 0 | 0 | — |
case-09 | pass→pass | 4,216 | 7,816 | +85% | 1 | 1 | 0% | 706 | 1,451 | +106% | 0 | 0 | — |
case-10 | fail→fail | 3,865 | 9,429 | +144% | 1 | 1 | 0% | 782 | 1,919 | +145% | 0 | 0 | — |
case-11 | pass→pass | 8,775 | 9,463 | +8% | 1 | 1 | 0% | 517 | 1,590 | +208% | 0 | 0 | — |
case-12 | pass→pass | 10,119 | 7,458 | -26% | 1 | 1 | 0% | 615 | 1,453 | +136% | 0 | 0 | — |
case-13 | fail→fail | 30,355 | 8,643 | -72% | 1 | 1 | 0% | 693 | 2,521 | +264% | 0 | 0 | — |
case-14 | fail→fail | 20,841 | 15,197 | -27% | 1 | 1 | 0% | 2,616 | 2,692 | +3% | 0 | 0 | — |
case-15 | pass→pass | 10,431 | 17,572 | +68% | 1 | 1 | 0% | 1,717 | 2,773 | +62% | 0 | 0 | — |
case-16 | pass→pass | 14,406 | 15,322 | +6% | 1 | 1 | 0% | 1,489 | 2,507 | +68% | 0 | 0 | — |
case-17 | pass→pass | 10,923 | 19,722 | +81% | 1 | 1 | 0% | 1,765 | 3,265 | +85% | 0 | 0 | — |
case-18 | fail→pass | 12,072 | 11,150 | -8% | 1 | 1 | 0% | 1,147 | 2,892 | +152% | 0 | 0 | — |
case-19 | fail→pass | 12,206 | 15,013 | +23% | 1 | 1 | 0% | 986 | 2,501 | +154% | 0 | 0 | — |
case-20 | fail→pass | 21,521 | 13,071 | -39% | 1 | 1 | 0% | 1,711 | 2,540 | +48% | 0 | 0 | — |
case-21 | fail→fail | 14,652 | 9,807 | -33% | 1 | 1 | 0% | 1,697 | 1,757 | +4% | 0 | 0 | — |
case-22 | fail→pass | 13,509 | 7,447 | -45% | 1 | 1 | 0% | 1,286 | 1,365 | +6% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 21 counted toward the lift figure. The other 1 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +27 percentage points is the difference between those two pass rates over the 21 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.