diff --git a/docs/src/submodules/Nonlinear/overview.md b/docs/src/submodules/Nonlinear/overview.md
index fdd7ca1f4c..daa4cfe10c 100644
--- a/docs/src/submodules/Nonlinear/overview.md
+++ b/docs/src/submodules/Nonlinear/overview.md
@@ -487,12 +487,14 @@ julia> struct Expression
 ```
 
 For each node `node` in the `.nodes` field, if `node.type` is:
+
  * `NODE_CALL_MULTIVARIATE`, we look up
    `MULTIVARIATE_OPERATORS[node.index]` to retrieve the operator
  * `NODE_CALL_UNIVARIATE`, we look up
    `UNIVARIATE_OPERATORS[node.index]` to retrieve the operator
  * `NODE_VARIABLE`, we create `MOI.VariableIndex(node.index)`
  * `NODE_VALUE`, we look up `values[node.index]`
+
 The `.parent` field of each node is the integer index of the parent node in
 `.nodes`. For the first node, the parent is `-1` by convention.
 
@@ -511,6 +513,16 @@ julia> expr = Expression(
        );
 ```
 
+The ordering of the nodes in the tape must satisfy two rules:
+
+ * The children of a node must appear after the parent. This means that the tape
+   is ordered topologically, so that a reverse pass of the nodes evaluates all
+   children nodes before their parent
+ * The arguments for a `CALL` node are ordered in the tape based on the order in
+   which they appear in the function call.
+
+#### Design goals
+
 This is less readable than the other options, but does this data structure meet
 our design goals?
 
@@ -524,9 +536,6 @@ easy to identify the _parent_ of any node. Therefore, we can use
 [`Nonlinear.adjacency_matrix`](@ref) to compute a sparse matrix that maps
 parents to their children.
 
-The tape is also ordered topologically, so that a reverse pass of the nodes
-evaluates all children nodes before their parent.
-
 ### The design in practice
 
 In practice, `Node` and `Expression` are exactly [`Nonlinear.Node`](@ref)