Chatbots have become a popular way to access all sorts of services via natural language. Many platforms and tools have been proposed for their construction, like Google’s Dialogflow, Amazon’s Lex or Rasa. However, most of them still miss integrated quality assurance methods like metrics. Moreover, there is currently a lack of mechanisms to compare and classify chatbots possibly developed with heterogeneous technologies.

To tackle these issues, we present Asymob a web platform that enables the measurement of chatbots using a suite of 20 metrics. The tool features a repository supporting chatbots built with different technologies, like Dialogflow and Rasa. Asymob’s metrics help in detecting quality issues and serve to compare chatbots across and within technologies. The tool also helps in classifying chatbots along conversation topics or design features by means of two clustering methods: based on the chatbot metrics or on the phrases expected and produced by the chatbot. A video showcasing the tool is available at https://www.youtube.com/watch?v=8lpETkILpv8.