  Large Language Models (LLMs) have shown a tremendous capacity for generating
literary text. However, their effectiveness in generating children's stories
has yet to be thoroughly examined. In this study, we evaluate the
trustworthiness of children's stories generated by LLMs using various measures,
and we compare and contrast our results with both old and new children's
stories to better assess their significance. Our findings suggest that LLMs
still struggle to generate children's stories at the level of quality and
nuance found in actual stories
