Each tool has a clearly distinct purpose with no overlap: calculate_readiness_score computes a score, get_health_summary aggregates data, get_tasks retrieves tasks, propose_schedule creates a schedule, and query_raw_logs runs SQL queries. The descriptions make it easy to differentiate them, preventing misselection.

The naming is mostly consistent with a verb_noun pattern (e.g., calculate_readiness_score, get_health_summary, get_tasks, propose_schedule), but query_raw_logs deviates slightly by using 'query' as a verb instead of a more standard action like 'get' or 'fetch'. However, the pattern is still readable and coherent overall.

With 5 tools, the server is well-scoped for a wellness planner domain. Each tool serves a specific function in the workflow—from data retrieval and calculation to scheduling and querying—without being too sparse or bloated, making it efficient for agents to use.

The tool set covers core wellness planning operations: calculating readiness, summarizing health data, managing tasks, proposing schedules, and querying raw logs. A minor gap is the lack of tools for updating or modifying tasks or health data (e.g., add_task, update_health_log), but agents can work around this using the existing tools for read and propose operations.