Four tools with clear action verbs and reasonable descriptions (avg 140 chars). All have input schemas with type definitions and parameter descriptions. However, output schemas are entirely undocumented, LLMs cannot predict response structure. Error handling is present but generic (no recovery guidance). Parameter constraints are loose (e.g., country accepts any string despite being ISO 2-letter code). No tool annotations (readOnlyHint, etc.). Composition is sound: each tool has one responsibility, but no pagination support for potentially large result sets (search_eu_law could return 45+ regulations).

• Document output schemas for all tools. E.g., validate_vat returns {valid: boolean, name: string, address: string, country: string, number: string}. Use JSON Schema in tool definition or explicit description.
• Add enum constraint to 'country' parameter in get_vat_rates: z.enum(['AT', 'BE', 'CY', ...]) instead of z.string(). Prevents invalid input and self-documents valid options.
• Add pagination to search_eu_law: accept 'limit' (1-50, default 20) and 'offset' (default 0) parameters. Return total_count and next_offset in response. Cap results at 20 by default.
• Enhance error messages with recovery guidance. E.g., 'Invalid VAT format. Expected 2-letter country code + 5-12 digits (e.g., DE123456789). Try validate_vat with a corrected number.' instead of generic 'Error'.
• Add tool annotations to schema: mark all four tools with readOnlyHint=true in the tool definition to signal safety to LLMs and enable optimizations.