Female hymenoptera are renowned for their ability to adjust offspring sex ratio to local mate competition. When two females share a patch, they frequently produce clutches that differ in size, the female with the larger clutch optimally producing a more female-biased sex ratio and vice versa. Females can base their sex allocation on their own clutch size only ("self-knowledge") or on both females' clutch sizes ("complete knowledge"). Few studies have genotyped offspring so that each mother's contribution can be considered separately while none has found that both sources of information are used simultaneously. We genotyped 2489 wasps from 28 figs and assigned their maternity to one of the two foundress females. We argue that likelihood is a very convenient method to compare alternative models, while fitness calculations help to appreciate the cost of maladaptation. We find that the pollinating fig wasp Platyscapa awekei simultaneously uses its own as well as the other females clutch size in allocating sex. Indeed, the complete knowledge model explains the data 36 times better than the self-knowledge model. However, large clutches contained fewer males than the optimal predictions leading to a median selection coefficient of 0.01. The study of sex ratios has been hailed a flagship of success of the optimality approach in evolutionary biology (West et al. 2000;West 2009). The main prediction that sex ratios should be skewed towards daughters as local mate competition between brothers increases (Hamilton 1967) is very well supported (King 1987;Herre et al. 1997;Hardy 2002). Even so, several authors have argued that while the theory seems to make qualitatively good predictions, it is quantitatively not accurate (Waage and Lane 1984;Orzack 1990 Orzack , 2002Greeff 2002;Nelson and Greeff 2009). Should we be concerned about these inaccuracies? The majority of researchers agree that the models used in the optimality approach are abstraction of reality formulated to guide our enquiries (Parker and Maynard Smith 1990). In fact, it is highly unlikely that deviations will not crop up! Many experiments reflect this view by only testing whether a proposed influential factor has the predicted qualitative effect on the trait. These tests are normally done, in Orzack's (1990) parlance, agnostically, in that the qualitative correspondence rather than the quantitative fit between predictions and data is tested.There are pitfalls to this qualitative approach: persistent oversight of discrepancies will lead to complaisance and eventually introduce blind spots in the field (Orzack 2002). Quantitative inaccuracies are compounded by the fact that crucial assumptions are frequently not confirmed (King 1987; Orzack 2002). In the case of sex ratios, the mating system is frequently not pinned down (Orzack 2002;Molbo et al. 2004). For instance, despite more than thirty years of sex ratio research on the wasp Nasonia vitripennis, the natural population structure was only investigated in two studies, one as recently as 2008 ( to a myopic vi...