Self-critique prompts the model to evaluate and criticize its own output before or after generation. By explicitly asking for problems, weaknesses, or improvements, the model can identify issues it might not catch in a single pass.
This technique leverages the model's ability to analyze text critically, turning it inward on its own responses.