{"data":{"kind":"file","path":"README.md","version_id":"ueseriiuo24z9f04dtxnzqgt","entry":{"name":"README.md","path":"README.md","is_directory":false,"size":1119,"modified_at":"2026-08-03T11:02:34.196000","content_hash":"20fc11ad6659277be11598ab1cd2189dd6a16612d031707ef66a3f51cd5da28f"},"entries":[],"content":"# Weather Forecast Environment\n\nA verifiers environment that evaluates LLM capabilities in meteorological reasoning, weather forecasting, and atmospheric science.\n\n## Tasks\n\nThe environment covers three difficulty levels:\n\n### Level 1 — Basic Weather Interpretation\n- Reading temperature, humidity, wind speed from data\n- Identifying weather conditions (sunny, cloudy, rainy)\n- Unit conversions (Celsius/Fahrenheit, km/h/mph)\n\n### Level 2 — Weather Analysis\n- Calculating wind chill and heat index\n- Identifying weather fronts and pressure systems\n- Predicting short-term weather changes from given data\n\n### Level 3 — Advanced Forecasting\n- Multi-day forecast reasoning from atmospheric data\n- Understanding of weather phenomena (El Nino, monsoons)\n- Severe weather identification and risk assessment\n\n## Scoring\n\n- **Accuracy**: Correctness of numerical calculations and factual answers\n- **Reasoning**: Quality of meteorological reasoning and explanation\n- **Completeness**: All parts of the question addressed\n\n## Usage\n\n```python\nimport verifiers as vf\nenv = vf.load_environment(\"bali/weather-forecast\")\n```\n","encoding":"utf-8","truncated":false,"total_bytes":1119},"status":null}