Server has 5 tools with basic schemas and descriptions, but significant gaps limit production readiness. All tools have descriptions (10-50 chars, mostly adequate) and input schemas with type definitions. However, parameter descriptions are sparse or missing context. Output schemas are undocumented, LLMs cannot predict response structure. Error handling is minimal (no recovery guidance, no categorization). No tool annotations (readOnlyHint/destructiveHint). register_service and rate_service are WRITE operations but lack confirmation/dry-run patterns. Naming is clear (verb_noun convention), but composition could be tighter, search_services and get_service overlap in intent.

• Document output schemas for all tools. Define response as structured JSON: {services: [{name, description, capabilities, tags, endpoint, rating: {average, count}}], total_count, next_cursor}. LLMs need to know field names and types to chain calls.
• Add tool annotations: register_service and rate_service should have destructiveHint=true; search_services, get_service, list_categories should have readOnlyHint=true. This signals intent without requiring LLM inference.
• Enhance error messages with recovery guidance. E.g., 'Service "xyz" not found. Try search_services(query="xyz") or list_categories() to discover available services.'
• Add confirmation step for register_service: return a dry-run response showing what would be registered, then require a confirm_register_service call. Prevents accidental overwrites.
• Expand parameter descriptions with constraints. E.g., 'score: Rating from 1 (poor) to 5 (excellent). Required.' and 'query: Search keyword (case-insensitive, matches name and description). Optional; if omitted, returns all services.'