Tibetan Jiu Chess, a recognized national intangible cultural heritage, is characterized by limited game data and significant parsing challenges. In this study, we leverage the retrieval-augmented generation (RAG) framework, prompt engineering, artificial intelligence (AI) agents, and large language models (LLMs) to construct a question-and-answer (Q&A) system tailored for Tibetan Jiu Chess. Additionally, we developed a specialized algorithm for Jiu Chess game parsing, which integrates with the LLM to enable intelligent and accurate game interpretation. Experimental results demonstrate that the Q&A system effectively addresses two types of Tibetan Jiu Chess questions, achieving notably higher accuracy in knowledge-based questions compared to baseline systems. This Q&A system not only addresses the gap in Tibetan Jiu Chess analysis but also pioneers a new approach to the preservation and transmission of Tibetan chess culture.
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