{"data":{"kind":"file","path":"README.md","version_id":"squbiijcqxguhyw5mwwbp4hm","entry":{"name":"README.md","path":"README.md","is_directory":false,"size":1270,"modified_at":"2026-08-03T08:00:30.839000","content_hash":"ffa035f20b06f1f8408f6698aa0e587e7e080b225e8bde5349b6485d83924f88"},"entries":[],"content":"# Weather Forecast Environment\n\nA verifiers environment for evaluating LLM capabilities in weather forecasting and meteorological reasoning.\n\n## Overview\n\nThis environment tests an LLM's ability to:\n- Interpret weather data (temperature, humidity, pressure, wind)\n- Make weather predictions based on atmospheric conditions\n- Understand meteorological concepts and terminology\n- Reason about weather patterns and climate phenomena\n- Convert between weather units and scales\n\n## Task Types\n\n1. **Data Interpretation**: Given raw weather observations, summarize conditions\n2. **Forecast Reasoning**: Given current conditions, predict short-term weather\n3. **Concept Explanation**: Explain meteorological phenomena clearly\n4. **Unit Conversion**: Convert between Celsius/Fahrenheit, hPa/inHg, km/h/knots\n5. **Severe Weather**: Identify severe weather risks from given conditions\n\n## Evaluation\n\n- **Accuracy**: Correctness of weather predictions and data interpretation\n- **Completeness**: Coverage of all relevant weather factors\n- **Reasoning Quality**: Logical chain from observations to conclusions\n- **Terminology**: Proper use of meteorological terms\n\n## Usage\n\n```python\nimport verifiers as vf\nenv = vf.load_environment(\"weather-forecast-env\")\n```\n\n## Version\n\n0.1.0\n","encoding":"utf-8","truncated":false,"total_bytes":1270},"status":null}