{
    "action": "tool_call",
    "reasoning": "The inspect_columns result shows null_count=0 for all 16 columns in the Dummy Data table. This means no columns have missing values. However, I should verify this with a SQL query to compute the exact null percentages, as the question asks for specific percentages and I need to ground this finding in a query result that will render as a table for the user.",
    "tool": "query_sql",
    "sql": "SELECT COUNT(*) as total_rows, COUNT(Name) as name_non_null, COUNT(Place) as place_non_null, COUNT(Age) as age_non_null, COUNT(Test) as test_non_null, COUNT(Gender) as gender_non_null, COUNT(Score) as score_non_null, COUNT(Flag) as flag_non_null, COUNT(Date) as date_non_null, COUNT(dhsgsgs) as dhsgsgs_non_null, COUNT(efks5453y) as efks5453y_non_null, COUNT(male) as male_non_null, COUNT(toronto) as toronto_non_null, COUNT(_ingestion_timestamp) as ingestion_ts_non_null, COUNT(_batch_id) as batch_id_non_null, COUNT(_source_file) as source_file_non_null, COUNT(_source_system) as source_system_non_null FROM raw.\"Dummy Data\"",
    "purpose": "Count non-null values for each column to calculate missing value percentages",
    "source": "raw"
}