The Few-Shot Task Pass Rate is a key evaluation metric for prompt engineering tasks in the fields of large language models and reasoning. It measures the proportion of tasks passed under few-shot prompting, thereby assessing few-shot prompting capabilities. It reflects the model's ability to learn task patterns from a small number of examples. This metric is typically reported as a percentage or a score between 0 and 1. It is widely used in relevant benchmarks and papers and effectively reflects model performance in this dimension. A higher value is better. It helps researchers and engineers quantify differences in actual model performance in prompt engineering scenarios, facilitating horizontal comparisons between different methods or model versions.