GitHub Actions (GHA) are a way to automate CI/CD workflows within the GitHub platform. The deep inte- gration of GHA into GitHub enables to automate a wide range of social and technical activities. In this study, we investigate workflow smells, i.e., characteristics in the workflow that possibly indicate a deeper problem. Through a mining study, we first expose a list of frequent change patterns in the workflows of 83 GitHub projects. We then manually analyze these frequent change patterns to understand the negative effects that the frequent changes try to remove. To validate the list of 22 potential workflow smells that we thus obtain, we carry out a contribution study with 32 projects on GitHub through pull requests that contain a fix to the candidate smell. By qualitatively analyzing the maintainers’ comments in 32 pull requests, we settle on 7 confirmed GHA workflow smells.