Researchers investigate the effectiveness of in-context learning (ICL) in multi-agent decision-making, finding that the benefits of ICL in strategic environments may be due to statistical extrapolation rather than refined reasoning. This study provides a reusable framework for evaluating LLM reasoning in recursive belief tasks and introduces a diagnostic tool using rational expectations equilibrium (REE).