Scored across 18 tools
Every tool has a clearly distinct purpose with no ambiguity. Tools are well-separated by scope (e.g., market-level, trader-level, protocol-wide, subgraph operations), and descriptions clearly differentiate them. For example, get_market_analytics provides comprehensive data for a single market, while get_global_stats offers aggregated protocol data, and there's no overlap in functionality.
Tool names follow a highly consistent verb_noun pattern throughout, using 'get_' for retrieval operations, 'compare_' for comparisons, 'search_' for searches, and 'query_' for raw queries. All names use snake_case uniformly, making them predictable and easy to understand, with no deviations in style or structure.
With 18 tools, the count is well-scoped for the server's purpose of providing analytics and data access for a prediction market protocol. Each tool earns its place by covering distinct aspects like market data, trader profiles, protocol stats, and subgraph operations, without feeling excessive or insufficient for the domain.
The tool surface offers complete coverage for the domain, including CRUD-like operations (e.g., get, search, query) across markets, traders, and protocol stats. It supports full lifecycle tracking (e.g., get_market_lifecycle, get_liquidity_events) and provides both aggregated and granular data, with no obvious gaps that would hinder agent workflows.