A data scientist is using a Large Language Model to automatically label thousands of customer reviews for a sentiment analysis project. Their goal is to create a dataset where each review is tagged with one of three exact labels: 'Positive', 'Negative', or 'Neutral'. However, their automated script keeps failing. They discover the model is producing a wide variety of responses, such as 'The sentiment of this text is clearly positive.', 'I'd say this is a negative review.', or simply 'Neutral'. Based on this information, analyze the likely cause of the script's failure and describe the specific modification you would make to the prompt to ensure the model produces consistent, machine-readable output.