# ClarifyCodeBench

Coding agents often fill in underspecified requirements with their own assumptions, producing code that looks correct but behaves in ways the user never intended, and fixing that later grows costly. CONTRA splits clarification into broad question generation followed by semantic filtering and execution-based qualification, keeping only questions whose two plausible answers yield stable behavioral differences, then uses interaction history to ask or stop. On ClarifyCodeBench it reaches the highest F1 with all four coding agents, 13.88 percentage points above the best baseline macro-average.

Coding agents often fill in underspecified requirements with their own assumptions, producing code that looks correct but behaves in ways the user never intended, and fixing that later grows costly. CONTRA splits clarification into broad question generation followed by semantic filtering and execution-based qualification, keeping only questions whose two plausible answers yield stable behavioral differences, then uses interaction history to ask or stop. On ClarifyCodeBench it reaches the highest F1 with all four coding agents, 13.88 percentage points above the best baseline macro-average.