01
Overview
drop agent transcript screenshot · 1200×500
The task
The agent receives a natural-language analytics question, such as "Which three product categories had the largest drop in revenue between Q1 and Q2 2024?", and a read-only SQLite database it has never seen. It must explore the schema with tools, write queries, and submit the exact result rows.
Why this environment
Rewards are verifiable: the grader compares result sets, so there is no LLM judge to game. The multi-turn budget rewards schema exploration and self-correction, not one-shot guessing.