Abstract Background Recommendations for good clinical practice have been reported to be difficult to apply in real life by primary care clinicians. This could be because the clinical trials at the origin of the guidelines are based on explanatory trials, conducted under ideal conditions not reflecting the reality of primary care, rather than pragmatic trials conducted under real-life conditions. The objective of this study was to evaluate how pragmatic are the clinical trials used to build the French High Authority of Health’s recommendations on the management of type II diabetes. Methods Trials from the 2013 Cochrane meta-analysis that led to the 2013 French High Authority of Health’s recommendations on the management of type II diabetes were selected. Each trial was analysed by applying the PRECIS-2 tool to evaluate whether the trial was pragmatic or explanatory, according to the nine domains of PRECIS-2. Each domain was scored between 1 (very explanatory) and 5 (very pragmatic) by two blinded researchers, and consensus was reached with a third researcher in case of discrepancy. Median scores were calculated for each of the nine domains. Results Twenty-three articles were analysed. Eight out of nine domains – namely eligibility, recruitment, setting, organisation, flexibility of delivery, flexibility of adherence, follow-up, and primary outcome – had a median score of less than 3, indicating a more explanatory design. Only the primary analysis domain had a score indicating a more pragmatic approach (median score of 4). In more than 25% of the articles, data to score the domains of recruitment, flexibility of delivery, flexibility of adherence, and primary analysis were missing. Conclusions Trials used to build French recommendations for good clinical practice for the management of type 2 diabetes in primary care were more explanatory than pragmatic. Policy-makers should encourage the funding of pragmatic trials to evaluate the different strategies proposed for managing the patient’s treatment according to HbA1C levels and give clinicians feasible recommendations.