Gradient, divergence and curl with covariant derivatives

For the gradient, your mistake is that the components of the gradient vary contravariantly. On top of that, there is a issue with normalisation that I discuss below. I don't know if you are familiar with differential geometry and how it works, but basically, when we write a vector as $v^\mu$ we really are writing its components with respect to a basis.

In differential geometry, vectors are entities which act on functions $f : M \rightarrow \mathbb{R}$ defined on the manifold. Tell me if you want me to elaborate, but this implies that the basis vectors given by some set of coordinates are $\partial_\mu = \frac{\partial}{\partial x^\mu}$ and vary covariantly. Let's name those basis vectors $e_\mu$ to go back to the "familiar" linear algebra notation.

Knowing that, any vector is an invariant which can be written as $\vec{V} = V^\mu \partial_\mu$. The key here is that it is invariant, so it will be the same no matter which coordinate basis you choose.

Now, the gradient is defined in Euclidean space simply as the vector with coordinates $\partial_i f = \partial^if$ where $i = \{x,y,z\}$. Note that in cartesian coordinates covariant and contravariant components are the same. So, the invariant quantity is $\vec{\nabla}f = \partial^ife_i$. Note that, from what we did before, the components of a vector are to be treated as contravariant.

Now, since this expression is invariant we get, in general coordinates $\vec{\nabla}f = \partial^\mu fe_\mu$. So what you are looking for when computing the components is $\partial^\mu f = g^{\mu\nu}\frac{\partial f}{\partial x^\nu}$. This gives $\vec{\nabla}f = \frac{\partial f}{\partial r} e_r + \frac{1}{r^2}\frac{\partial f}{\partial \theta} e_\theta +\frac{1}{r^2 \sin^2\theta}\frac{\partial f}{\partial \phi} e_\phi$. This is still not what we're looking for.

This is due to the fact that the basis vectors are not normalised. Indeed, take a specific vector $e_I$. His components are $\delta^\mu_I$ by definition (it's a basis vector). Then, $|e_I|^2 = e_I^\mu e_I^\nu g_{\mu\nu} = g_{II}$. Great then ! Using $e_i' = e_i/\sqrt{g_{ii}}$ as normalised base vectors, we get the right answer : $\vec{\nabla}f = \frac{\partial f}{\partial r} e_r' + \frac{1}{r}\frac{\partial f}{\partial \theta} e_\theta' +\frac{1}{r \sin\theta}\frac{\partial f}{\partial \phi} e_\phi'$

Let's move onto the divergence. It seems easier since it's a scalar, there's no basis vector to mess around with. Well, actually there are still some problem attached to that. Your formula is right, again, except that when you write the invariant formula $\nabla_\mu V^{\mu}$ you implicitly use the basis that we defined earlier. This means that you are not working on a normalised basis. We know that the $\vec{V}$ you used is $\vec{V} = V^\mu e_\mu = V^\mu \sqrt{g_{\mu\mu}}e_\mu'$. So to compare formula you have to introduce the vector with respect to the normalised coordinates, $A^\mu= V^\mu\sqrt{g_{\mu\mu}}$. I'll let you plug it in your (correct) formula to see that it works.

To conclude, your formula for the curl should be right. Just be careful to use the right normalisations for the vectors and you should be fine (also be careful of the tensorial form of the levi-civita tensor, which involves the determinant of the metric). I have not the faith to do the calculations for you, but you definitely should try it to ensure yourself you understood it well.

P.S: Just for completeness, for the divergence there is a quite useful formula which is also used in Sean Caroll book : $\vec{\nabla}\cdot\vec{V} = \frac{1}{\sqrt{g}}\partial_\mu(\sqrt{g}V^\mu)$, useful when you're too lazy to compute Christoffels.

The gradient is a vector, not a covector, hence :

\begin{equation} \vec{\nabla} f = \nabla^\mu f = g^{\mu\nu} \nabla_\nu f = g^{\mu\nu} \partial_\nu f \end{equation}