Sign language is a priceless means of communication for deaf and hard-of-hearing people to fully enable them to participate in society and interact with others. This study introduces a novel universal sign language system that uses the Gesture-script to generate a detailed description of gestures in videos, which involve continuous movement of hands, arms, heads, and body language. Subsequently, we input this description into a Large Language Model (LLM) to interpret sign language. We deployed a few-shot prompting technique for LLM, enabling it to precisely transfer the sign videos into corresponding sentences in natural language. Furthermore, the Few-shot prompting technique enables our system to interpret multiple types of sign language without pre-training or fine-tuning.