The recommendation of tasks for newcomers within a software project through good first issues is being done within the domain of software development, such as on Github platform. These issues aim to help newcomers identify tasks that are suitable for them and their level of expertise within the project. This thesis report investigates the effectiveness regarding developer onboarding and task completion of good first issues by data mining a set of 105 repositories and manually analyzing at most 30 good first issues and 30 initial commits per sampled project. It was found that, although good first issues are effective at developer onboarding, and developers perceive good first issues as being useful, changes can be made to the types of tasks suggested as good first issues to match the types of initial contributions made by newcomers. It was also found that developers with less than a year of experience favored documentation- related contributions for their first commit to a project.