Creating a cast of characters by attending to their relational dynamics is a critical aspect of most long-form storywriting. However, our formative study (N=14) reveals that writers struggle to envision new characters that could influence existing ones, balance similarities and differences among characters, and intricately flesh out their relationships. Based on these observations, we designed Constella, an LLM-based multi-agent tool that supports storywriters' interconnected character creation process. Constella suggests related characters (FRIENDS DISCOVERY feature), reveals the inner mindscapes of several characters simultaneously (JOURNALS feature), and manifests relationships through inter-character responses (COMMENTS feature). Our 7-8 day deployment study with storywriters (N=11) shows that Constella enabled the creation of expansive communities composed of related characters, facilitated the comparison of characters' thoughts and emotions, and deepened writers' understanding of character relationships. We conclude by discussing how multi-agent interactions can help distribute writers' attention and effort across the character cast.

翻译：在长篇故事创作中，通过关注角色间动态关系来构建角色群是至关重要的环节。然而，我们的形成性研究（N=14）表明，作者在以下方面存在困难：构想可能影响现有角色的新角色、平衡角色间的相似性与差异性，以及细致刻画角色关系。基于这些观察，我们设计了Constella——一个基于大语言模型的多智能体工具，用以支持故事作者的互连角色创作过程。Constella通过以下功能实现支持：推荐关联角色（好友发现功能）、同步揭示多个角色的内心世界（日志功能），以及通过角色间互动展现关系（评论功能）。我们为期7-8天的故事作者部署研究（N=11）表明，Constella能够帮助创建由关联角色构成的扩展社群，促进角色思想与情感的比较，并深化作者对角色关系的理解。最后，我们讨论了多智能体交互如何帮助作者将注意力和创作精力分配到整个角色群中。