Ruminant production systems have been facing the sustainability challenge, namely, how to maintain or even increase production while reducing their environmental footprint, and improving social acceptability. One currently discussed option is to encourage farmers to follow agroecological principles, that is, to take advantage of ecological processes to reduce inputs and farm wastes, while preserving natural resources, and using this diversity to increase system resilience. However, these principles need to be made more practical. Here, we present the procedure undertaken for the collaborative construction of an agroecological diagnostic grid for dairy systems with a focus on the mountain farming relying on the use of semi-natural grasslands. This diagnosis will necessarily rely on a multicriteria evaluation as agroecology is based on a series of complementary principles. It requires defining a set of criteria, based on practices to be recommended, that should be complied with to ensure agroecological production. We present how such agroecological criteria were identified and organized to form the architecture of an evaluation model. As a basis for this work, we used five agroecological principles already proposed for animal production systems. A group of five experts of mountain production systems and of their multicriteria evaluation was selected, with a second round of consultation with five additional experts. They first split up each principle into three to four generic sub-principles. For each principle, they listed three to eight categories of state variables on which the fulfilment of the principle should have a positive impact (e.g. main health disorders for the integrated health management principle). State variables are specific for a given production, for example, dairy farms. Crossing principles with state variables enabled experts to build five matrices, with 75 cells relevant for dairy systems. In each cell, criteria are specific to the local context, for example, mountain dairy systems in this study. Finally, we discuss the opportunities offered by our methodology, and the steps remaining for the construction of the evaluation model.