Server has 5 tools with basic schemas and descriptions, but significant gaps limit production readiness. All tools have descriptions (10-50 chars, below the 50-200 char baseline for LLM optimization) and input schemas with type definitions. However, descriptions are generic and lack actionable context. Parameter descriptions are minimal or missing context about constraints, formats, and dependencies. No output schemas documented. Error handling is absent, no recovery guidance, categorization, or actionable error messages. Tools like 'query_custom_service' and 'execute_query' expose dangerous operations (WRITE risk) without confirmation patterns or permission gates. Naming is verb-first (good), but descriptions do not explain WHEN to use each tool or what distinguishes them from similar tools.

• Expand all tool descriptions to 50-200 characters. Include WHAT the tool does, WHEN to use it, and what it returns. Example: 'Get current date/time in specified format and timezone. Use this to timestamp events, schedule tasks, or display times to users. Returns ISO 8601 string by default.'
• Document output schemas for all tools. Specify field names, types, and whether results are paginated. Example: get_datetime returns {timestamp: string, timezone: string, format: string}.
• Add parameter constraints and formats to descriptions. Example: 'expression: Mathematical expression using +, -, *, /, %, ^ operators. Example: 2 + 3 * 4. Max 500 chars.'
• Implement confirmation patterns for destructive tools (query_custom_service, execute_query). Add a dry_run parameter or require explicit confirmation before executing. Log all calls with user/agent ID, parameters, and result for audit trails.
• Add permission gates and scope declarations. Verify caller has authority before executing SQL or HTTP requests. Declare required permissions (e.g., 'read:database', 'write:http') so agents can be configured with least privilege.