counterfactual-reasoning

What problem does it solve?

Helps you systematically challenge a research conclusion by generating plausible alternative explanations and checking whether your evidence actually supports your claims, before you submit.

Core Features & Use Cases

• Counterfactual decomposition: Breaks down your conclusion into core claim, causal direction, scope assumptions, proposed mechanism, and evidence-to-claim inference distance.
• Alternative explanation enumeration: Produces competing threats across confounding variables, reverse causation, selection bias, observer effects, and alternative mechanisms, including severity and likely handling status.
• Boundary and reviewer simulation: Tests representativeness, time robustness, and context transferability, then simulates multiple reviewer stances with tailored response strategies.

Quick Start

Ask an AI to run counterfactual reasoning by providing your core conclusion, its key evidence, any known weaknesses, your research design overview, and the target journal so it can output a 4-stage pressure test.