Linear programming, shadow price range
The shadow price is formally not the increase in the objective function for relaxing a constraint by a single unit, but by an infinitesimal relaxation. In the world of linear programming it can be valid for up to a unit but it doesn't have to be. In your example problem it is actually not.  This becomes clearest when we use pictures. 

I am going to assume that you were maximizing, not minimizing your objective function and furthermore that you have two additional constraints that you hadn't actually stated: 

$K\geq0$ and
$S\geq0$

That would result in the following graphic with K on the y-axis and S on the x-axis, and the optimum at the red dot. The black dotted lines are isoquants of Z, for Z=100, Z=150 and Z=200.



The feasible region is made up of the x and y axis, the blue line from the y-axis up to the crossing, and the orange line from that point on to the x axis.

Let us now relax your constraint $K+2S\leq6$ by one unit, as you propose. In essence this means that the constraint becomes $K+2S\leq7$ and when we draw the new constraints we get:



Turns out that the new constraint no longer plays a role in determining the optimum! The optimum is now determined by the constraints: $S\geq0$ and $2K+3S\leq10$.

The answer to your question should now be clear: the shadow price is valid up to the point where that particular combination of constraints continues to determine the optimum. In this case that means that you can increase 6 to $6\frac{2}{3}$, for a corresponding increase in the objective function of $10*\frac{2}{3}=\frac{20}{3}$  After that point the combination of constraints no longer determines the optimum.

As a side point let me add that at least the Excel solver (and I expect therefore many other solvers too) report up to which point you can relax the constraints before the optimum is determined by another set of constraints.