Each tool targets a distinct entity or aggregation level: database schema, customer counts, product sales rankings, category revenue, total revenue, and customer leaders. Even though get_customer_metrics and get_order_leaders both involve customers, their purposes (country-level counts vs. individual customer extremes) are clearly separated. No two tools are likely to cause misselection.

All tool names follow the consistent pattern 'get_' followed by a descriptive noun phrase, using snake_case throughout. Examples: get_database_schema, get_product_sales, get_revenue_by_period. This uniform phrasing makes the set predictable and easy to navigate.

With 6 tools, the server is well-scoped for a shop analytics use case. It covers the essential query types without unnecessary proliferation, and each tool earns its place by addressing a distinct analytical question. The count is within the ideal range for a focused server.

The tool set covers key analytics workflows: schema inspection, customer metrics, product and category performance, total revenue, and top customer identification. Minor gaps include lack of time-series revenue breakdown (e.g., by day/month) and no list of customers beyond the leader, but the core analytical needs are met. These omissions are workable around.