The original question slightly mischaracterizes Greenbaum's description. On page 20, Greenbaum states (Eq. 3.10) that the $F_k$ correspond to products of elements from $\mathcal{G}$. They are not necessarily themselves elements of $\mathcal{G}$. This is important. In the two examples that Greenbaum gives (which the original question mentions), only the second one actually uses a set $\{F_k\}$ that is in 1:1 correspondence with $\mathcal{G}$. The first example has a smaller set of native gates in $\mathcal{G}$, and requires at least one $F$ that is a product of gates from $\mathcal{G}$.
In general, a gate set $\mathcal{G} = \{\rho,M,G_1\ldots G_k\}$ is "complete" if and only if:
- A set of density matrices that span the space of $d\times d$ matrices can be produced by applying products of gates from $\mathcal{G}$ to the initial state $\rho$.
- A set of POVM effects that span the space of $d\times d$ matrices can be produced by applying products of gates from $\mathcal{G}$ to the effects $E_j$ in the POVM $M = \{E_j\}$.
When viewed as a condition on the states and effects that can be constructed, this is the requirement of informational completeness that appears throughout the literature on tomography. But as a condition on gate sets, it is a little nontrivial and does not have a simple mathematical definition in the literature. For example, it's worth observing that this is not strictly a condition on the gates $\{G_k\}$! The gate set contains $\rho$ and $M$ too. If the gates act on a single qubit and generate a dihedral group, then it's possible to generate informationally complete input states and final measurements unless $\rho$ and $M$ commute with $\sigma_z$.
Most single-qubit gate sets are sufficient to generate spanning SPAM sets. If your gate set generates any unitary 2-design (e.g. the Cliffords), then it's guaranteed to be complete. It's pretty hard not to generate the Cliffords, so this is a useful rule of thumb. If your gate set doesn't generate the Cliffords, caveat emptor and you may have to do some math.