Methods and systems for using natural language processing and machine-learning algorithms to process vehicle-service data to generate metadata regarding the vehicle-service data are described herein. A processor can discover vehicle-service data that can be clustered together based on the vehicle-service data having common characteristics. The clustered vehicle-service data can be classified (e.g., categorized) into any one of a plurality of categories. One of the categories can be for clustered vehicle-service data that is tip-worthy (e.g., determined to include data worthy of generating vehicle-service content (e.g., a repair hint). Another category can track instances of vehicle-service data that are considered to be common to an instance of vehicle-service data classified into the tip-worthy category. The vehicle-service data can be collected from repair orders from a plurality of repair shops. The vehicle-service content generated by the systems can be provided to those or other repair shops.