Repair describes the process through which participants in conversation address problems in speaking, understanding, and hearing. In interactions with AI-driven chatbots, repair helps users clarify their intents and addresses problems in understanding intent experienced by chatbots. This paper represents the first attempt to describe repair strategies in a task-oriented text-based chatbot from a user-centred perspective. It is based on the analysis of simulated user interactions with a chatbot facilitating health appointment bookings. The analysis shows that the self-repair strategies which users draw on most frequently (e.g. rephrasing) are not necessarily the ones which prompt the bot to provide relevant responses, whereas more successful self-repair strategies (e.g. restating the intent) tend to be more opaque to users and thus used relatively infrequently. This suggest that the notion of communicative competence needs to be re-thought for conversational AI and that communication skills for AI need to be taught explicitly.