query_table

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Run an EXACT, deterministic query over ONE tabular file (a CSV, or the first table of a spreadsheet/PDF/Word document). Use this instead of ask_docs whenever the question needs COUNTING, SUMMING, AVERAGING, MIN/MAX, FILTERING, or exact row lookups over structured data ('how many rows...', 'total amount by region', 'list orders where status is failed') - semantic search undercounts tables, while this executes over EVERY row and returns exact numbers. Use ask_docs for prose/meaning questions and get_file to read a whole document. The `query` argument is a JSON object: { select?: [column names to return as raw rows], where?: [{col, op, value}, ...] filters combined with AND - ops eq | neq | contains compare text case-insensitively, gt | gte | lt | lte compare numerically (rows whose cell is not a number are skipped and counted in skippedNonNumeric), groupBy?: 'column' gives one result row per distinct value, aggregates?: [{fn, col}] with fn count | sum | avg | min | max ('col' required except for count), limit?: max raw rows (default 50, max 200) }. Column names match the file's header row case-insensitively. Examples: {"where":[{"col":"status","op":"eq","value":"failed"}],"aggregates":[{"fn":"count"}]} counts failed rows; {"groupBy":"region","aggregates":[{"fn":"sum","col":"amount"}]} totals amount per region; {"select":["name","email"],"where":[{"col":"country","op":"eq","value":"FR"}]} returns the matching rows. If you name a column that does not exist, the error lists the file's real columns - retry with one of those. Read-only; always allowed.