parameter [@Weinberg] – or $3$ of similar size [@Birse:2005um; @Birse:2009my] – or $3$, but with different weights [@PavonValderrama:2005wv; @PavonValderrama:2005uj; @Valderrama:2009ei; @Valderrama:2011mv] – or $1$ [@Long:2011xw; @Long:2012ve]. To bring it to a boil: If all proposals are renormalised and fit $\mathrm{NN}$ data with the same $\chi^2$, the one with the least number of parameters wins.

For the sake of this note, I am agnostic about this dispute. Rather, I propose to test if a predicted convergence pattern is reflected in the answers, i.e. if a proposed power counting is consistent. On a historical note, the origin of these remarks goes back to publications in 2003 and 2005 [@Bedaque:2002yg; @improve3body], and to lectures at the 2008 US National Nuclear Physics Summer School [@NNPSS]. When the issue was revisited at two more recent workshops [@Saclay; @Benasque], its conclusions were generally perceived as not immediately straightforward or widely known. Input on some aspects was also provided for two recent publications [@Furnstahl:2014xsa; @Epelbaum:2014efa]. It seems therefore fitting to present the test in the form of an expanded Technical Note. This article summarises an upcoming publication [@hgrie].

The Test: Turning Cutoff Dependence into an Advantage
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Assume we calculated an observable ${\mathcal{O}}$ up to and including 