When Does Personality Composition Matter for Multi-Agent LLM Teams?

Computer Science > Artificial Intelligence [Submitted on 25 Jun 2026] When Does Personality Composition Matter for Multi-Agent LLM Teams? Aryan Keluskar, Amrita Bhattacharjee, Huan Liu Personality prompting shapes how large language models communicate, yet whether these behavioral shifts affect objective task outcomes remains under-explored. Prior work shows that agents prompted with low agreeableness produce adversarial language, while those prompted with high agreeableness become cooperative, but the relationship between communication style and task performance has not been systematically examined across multiple domains. In this work, we investigate whether personality composition matters for multi-agent team performance by manipulating personality traits across frontier LLMs on three task domains: structured coding, open-ended research collaboration, and competitive bargaining. We find that personality effects depend critically on task structure. In coding tasks, low agreeableness leads to large communication shifts that have little effect on milestone completion. In open-ended collaboration and bargaining, the same manipulation substantially degrades performance. We discuss implications for multi-agent system design and the limits of personality manipulation. Comments: 20 pages, 6 figures Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2606.27443 [cs.AI]   (or arXiv:2606.27443v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2606.27443 Focus to learn more Submission history From: Aryan Keluskar [view email] [v1] Thu, 25 Jun 2026 18:13:33 UTC (255 KB) Access Paper: HTML (experimental) view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)