A research paper proposes a model-agnostic framework to repurpose deep limit order book forecasting models for scenario-conditioned market impact modeling. This allows for quantifying the effects of counterfactual order book messages without retraining the models. This advancement has implications for AI agents operating in financial markets, enabling them to better understand and respond to market scenarios.