Three weather tools with minimal quality. All descriptions are in Turkish (non-English), making them inaccessible to most LLM agents. Tool names lack clarity: 'is_outdoor_weather_good' conflates evaluation with boolean return (unclear if it returns true/false or a detailed assessment). Input schemas present but trivial (single string param, no constraints). No output schemas documented. No error handling guidance. No parameter validation rules. Tools appear to be inferred from Spring AI framework rather than explicitly defined with full MCP schemas.

• Translate all tool descriptions to English. Example: 'get_current_weather: Retrieves current weather data (temperature, humidity, wind, precipitation) for a specified city or location.'
• Document output schemas for each tool. Specify fields returned (e.g., temperature, unit, humidity, wind_speed, condition) with types and descriptions.
• Add constraints to 'location' parameter: enum of supported cities, or a regex pattern (e.g., '^[A-Za-z\s]{2,50}$'). Include examples in description.
• Rename 'is_outdoor_weather_good' to 'evaluate_outdoor_suitability' and clarify return type in description (e.g., 'Returns a suitability score 0-100 and a recommendation string').
• Add error handling guidance: 'If location is not found, returns error with list of nearby supported locations. If API is unavailable, returns timeout error, retry after 30 seconds.'

Inferred effective spec: <=2025-11-25.

• Relies on Logging (deprecated) - log to stderr or use OpenTelemetry