Server provides 8 agriculture-focused tools with complete input schemas and descriptions. All tools are READ_ONLY and well-scoped. However, descriptions lack LLM-optimization guidance (many exceed 200 chars), output schemas are not documented, and error handling is absent from tool definitions. Parameter descriptions are present but generic. No tool annotations (readOnlyHint, etc.) despite all being read-only. Naming is clear and verb-based (soil_conditions, crop_weather_forecast, etc.), following verb_noun convention. Tools are properly composed with single responsibilities.

• Document output schemas for all tools. Add a 'Returns' section to each tool description specifying JSON structure. Example: 'Returns {soil_temp_0cm: float, soil_moisture_0_1cm: float, et0_mm: float, timestamp: ISO8601}'. This enables LLMs to extract and chain results.
• Condense tool descriptions to 100-150 characters. Rewrite soil_conditions from 280 chars to: 'Soil temperature (0-54cm depth), moisture, and evapotranspiration forecast. Use for irrigation planning and seeding decisions.' Trim climate_history similarly.
• Add readOnlyHint annotation to all 8 tools in FastMCP registration. This signals to clients that tools are safe to call without confirmation and enables caching optimizations.
• Enhance parameter descriptions with format constraints. Change 'Breitengrad' to 'Latitude in decimal degrees (-90 to 90, e.g., 52.52)'. Change 'Vorhersage-Tage' to 'Forecast days (1-16, default 7). API caps at 16 days.'
• Add error recovery hints to tool descriptions. Example for soil_conditions: 'If coordinates invalid, verify lat/lon format. If API timeout, retry after 30s. If no data, location may lack soil sensors.'