47 tools with consistent naming (verb_noun pattern: get_*) and basic descriptions. However, critical gaps undermine quality: (1) Input schemas visible but parameter descriptions are minimal or generic ('Optional date in format YYYYMMDD' repeated 30+ times); (2) No output schemas documented, LLMs cannot plan downstream calls or extract fields; (3) No error handling guidance, tools return raw API responses without recovery hints; (4) Parameter constraints not formalized (date format stated in text, not regex/pattern); (5) Many tools accept optional parameters with unclear defaults or side effects. Naming is strong (all verb_noun, action-oriented), but descriptions lack LLM-optimization depth (most 50-100 chars, below 194-char baseline for A+ tools). Schema completeness is low, input types present but output types absent.

• Document output schemas for all 47 tools. For each, specify: field names, types (string|number|array|object), required vs optional fields, and example values. Use JSON Schema format in tool registration.
• Enhance parameter descriptions from generic to actionable. Example: 'date (YYYYMMDD): Optional. If omitted, returns current/latest data. Format: 4-digit year + 2-digit month + 2-digit day (e.g., 20240115 for Jan 15, 2024).'
• Add error handling guidance to tool descriptions. Example: 'If date is invalid, returns 400 with message. Try get_exchange_rates() without date param to see available dates.' Implement try-catch in tool code to return structured error objects with recovery hints.
• Formalize date constraints as regex patterns in JSON Schema (pattern: '^\d{8}$') instead of relying on text descriptions. Add min/max for numeric params (e.g., limit: 1-100).
• Remove or restrict call_api tool. If raw API access is needed, rename to make_nbu_api_request and add warnings in description that it bypasses validation. Better: remove it and ensure all common endpoints have dedicated tools.