This server defines 2 weather tools with reasonable clarity. Tool names follow verb_noun convention (get-alerts, get-forecast). Both tools have descriptions and input schemas with proper JSON Schema structure. However, there are notable gaps: output schemas are NOT documented (only TextContent responses are returned with no schema definition), parameter descriptions are minimal (latitude/longitude lack range constraints, state parameter lacks guidance on validation), and error handling is present but not well-integrated into the tool interface. The server returns plain text responses rather than structured objects, making it harder for LLMs to chain calls. No tool annotations (readOnlyHint, destructiveHint, idempotentHint) are declared. The code shows decent input validation (latitude -90 to 90, longitude -180 to 180, state length check) but these constraints are not formally declared in the schema, they appear only in the implementation.

• Add formal constraints to parameter schemas: add pattern: '^[A-Z]{2}$' to state param; add minimum/maximum to latitude (-90/90) and longitude (-180/180) in the JSON Schema inputSchema.
• Document output schema explicitly. Define the structure of alert and forecast TextContent responses (e.g., a structured JSON object with fields like 'alerts': [{event, area, severity, ...}]) and return it as structured data instead of plain text formatting.
• Enhance parameter descriptions to match rubric baseline (72 chars avg): 'state: Two-letter US state code (e.g. CA, NY). Must be uppercase. Example: CA returns active alerts for California.' and 'latitude: Geographic latitude in decimal degrees (-90 to 90). Example: 37.7749 for San Francisco.'
• Add tool annotations to the tool definitions: include 'readOnlyHint': true in both tool definitions to explicitly declare they do not modify state.
• Implement pagination for get-alerts: add 'limit' (default 20, max 100) and 'offset' (default 0) parameters, and return {alerts: [...], total: N, offset, limit} to support large result sets.
• Standardize error responses: return a consistent error object {error: string, code: string, recoveryHint: string} instead of plain text, so LLMs can parse failures reliably.
• Add recovery guidance to error messages per pattern:recovery-guide. E.g., 'Failed to retrieve grid point: location may not be in US. Try search_locations() first.' instead of just 'Failed to retrieve grid point data'.

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

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