Studies have shown that when we operate the cursor on a computer, several factors such as the type of device used (i.e. mouse or touchpad), aging (young vs. old) or motor-impairment can hinder performances. More precisely, using the touchpad can be difficult for any user, even for the most basic tasks, due to the absence of scrolling wheel and the reduced amplitude of cursor movement. To cope with these issues, I developed a set of tools to increase the usability of the touchpad by analyzing mouse-tracking data. More specifically, several movement patterns or cues were predefined and when they were detected, they would trigger the auto-completion of the related task which includes navigating on a web browser, selecting text and scrolling. The usability experiment conducted to assess the ease-of-use of the created tools and to compare the performances of participants showed promising results. Participants appreciated the help of the auto-completion tools and when they were able to trigger these tools, they were significantly faster. In particular, when moving the cursor to the URL address bar they even outperformed Fitts’ law predictions. However, it appeared that participants needed several attempts to draw certain cues correctly hence a longer completion time.