I need to identify all categorical columns across the dataset and count their distinct values. From the evidence, I can see column metadata that shows `rough_kind` classifications, but I need to query systematically across all tables. Let me write a comprehensive query to profile all categorical columns: ```json { "action": "tool_call", "reasoning": "The evidence shows column metadata with rough_kind='categorical' for many columns. I need to query the meta.columns catalog to find ALL categorical columns across the dataset, then compute their distinct counts. I'll use the metadata that's already available rather than scanning each raw table individually.", "tool": "query_sql", "args": { "sql": "SELECT table_name, column_name, phys_type, distinct_count, approx_distinct_count FROM meta.columns WHERE rough_kind = 'categorical' ORDER BY COALESCE(distinct_count, approx_distinct_count, 0) DESC, table_name, column_name", "purpose": "Get distinct value counts for all categorical columns across the dataset" } } ```