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Scored across 6 tools
Each tool owns a distinct job: describe_lake for metadata/contract, resolve_symbol for identifier lookup, query_bars for prices, query_fundamentals for statements, query_dataset for all other datasets, and run_sql for aggregation. The descriptions actively cross-route ('Bars go through query_bars... for cross-sectional ranking use run_sql'), neutralizing the one potential overlap between query_dataset and run_sql.
All names follow a consistent snake_case verb_noun pattern (describe_lake, resolve_symbol, query_bars, query_fundamentals, query_dataset, run_sql). Verbs vary appropriately by action rather than arbitrarily, so the convention is predictable and readable.
Six tools is well-scoped for a data lake spanning dozens of datasets: rather than one tool per dataset, the design consolidates with query_dataset and run_sql, so every tool earns its place. Neither bloated nor thin.
The read lifecycle is essentially complete — discover contents, resolve identifiers, query prices, financials, and arbitrary datasets, then aggregate in SQL with adjustment views provided. Minor gap: no explicit per-dataset column/schema discovery tool, though DuckDB views via run_sql largely fill it.
