The global workforce is urged to constantly reskill, as technological change favours particular new skills while making others redundant. But which skills are most marketable and have a sustainable demand? We propose a model for skill evaluation that attaches a market value to a set of 962 digital skills based on near real-time online labour market data. We demonstrate that the value of a specific skill is strongly determined by complementarity – that is with how many other high-value skills a competency can be combined. Most importantly, we show that the value of a skill is relative, as it depends on the capacities it is combined with. For most skills, their value is highest when used in combination with skills of the same type. We illustrate our model with a set of AI skills that are particularly valuable because of their strong complementarities, and also because of the significant increase in their demand in recent years. Finally, we contrast our skill premia with automation probabilities and find that some skills are very susceptible to automation despite their high market value. The model and metrics of our work can inform the policy and practice of digital re-skilling to reduce labour market mismatches. In cooperation with online platforms and education providers, researchers and policy makers should consider using this blueprint to provide learners with personalised skill recommendations that complement their existing capacities and fit their occupational background.