TimeServer has 3 tools with basic descriptions and parameter schemas, but significant gaps prevent higher scores. All tools have descriptions (10-100 chars baseline met), and parameters include type and description fields. However, output schemas are completely undocumented, LLMs cannot predict return structure. Error handling is minimal (string error messages, no recovery guidance). No input validation constraints (enums, ranges, patterns) despite timezone parameter accepting arbitrary strings. Tools are read-only and simple, but lack the rigor expected for production use.

• Document output schemas for all three tools. E.g., get_current_time returns {time: string, timezone: string, utc_offset: string}. This enables LLMs to chain calls and extract fields correctly.
• Add enum constraints to timezone and format parameters. Replace free-form strings with validated enums: timezone from pytz.all_timezones, format from ['full', 'short', 'iso'].
• Enhance error messages with recovery guidance. Instead of 'Error: Zona horaria ... no válida', return 'Invalid timezone. Call list_timezones(region="America") to see available zones, or use a standard name like America/Mexico_City.'
• Implement pagination for list_timezones. Accept limit (1-100, default 20) and offset parameters. Return {timezones: [...], total: int, next_offset: int|null} to handle large result sets.
• Add input validation in tool implementations. Validate timezone against pytz.all_timezones before calling datetime.now(). Return structured error objects {error: string, code: string, suggestion: string} instead of plain text.