diff --git a/ethosu/vela/supported_operators.py b/ethosu/vela/supported_operators.py
index 46f7a5d..ccf6104 100644
--- a/ethosu/vela/supported_operators.py
+++ b/ethosu/vela/supported_operators.py
@@ -25,6 +25,7 @@
 from .operation import get_slice_offsets
 from .operation import Op
 from .tensor import check_quantized_tens_scaling_equal
+from .tflite_mapping import BUILTIN_OPERATOR_UNKNOWN
 from .tflite_mapping import optype_to_builtintype
 
 
@@ -37,6 +38,15 @@
     return docstring
 
 
+def _optype_formatter(op_list):
+    # Convert internal op types to external names
+    output = map(optype_to_builtintype, op_list)
+    # Remove UNKNOWNs
+    output = (x for x in output if x is not BUILTIN_OPERATOR_UNKNOWN)
+    # Order alphabetically
+    return sorted(output)
+
+
 class SupportedOperators:
     # Categorised lists of supported operators
     npu_pre_ops = set((Op.SplitSliceRead,))
@@ -99,6 +109,10 @@
     filter_range = (1, 8)
     filter_height_range = (1, 256)
     filter_product_range = (1, 256 * 256)
+    # Ordered, external names of op types for the constraint reasons
+    docstring_shapeless_input_ops = _optype_formatter(shapeless_input_ops)
+    docstring_supported_int32_tensor_ops = _optype_formatter(supported_int32_tensor_ops)
+    docstring_supported_fused_activations = _optype_formatter(supported_fused_activations)
 
     def __init__(self):
         # Setup the generic constraints. Note: the order matters
@@ -279,7 +293,7 @@
         return valid, f"Output Tensor '{ofm.name}' is scalar"
 
     @classmethod
-    @docstring_format_args([shapeless_input_ops])
+    @docstring_format_args([docstring_shapeless_input_ops])
     def constraint_tens_input_scalar(cls, op):
         "Scalar Input tensors are only valid for op type: {}"
         valid = True
@@ -320,7 +334,7 @@
         return valid, ", ".join(extra)
 
     @classmethod
-    @docstring_format_args([supported_int32_tensor_ops])
+    @docstring_format_args([docstring_supported_int32_tensor_ops])
     def constraint_tens_int32_ops(cls, op):
         "Tensors which are int32 are only valid when op type is: {}"
         valid = True
@@ -377,7 +391,7 @@
         return valid, ", ".join(extra)
 
     @classmethod
-    @docstring_format_args([supported_fused_activations])
+    @docstring_format_args([docstring_supported_fused_activations])
     def constraint_faf(cls, op):
         "The fused activation function (if present) must be one of type: {}"
         if op.activation is None: