writer edits

Author: PatrickFarley

articles/cognitive-services/personalizer/includes/quickstart-sdk-nodejs.md

@@ -71,28 +71,28 @@ Personalizer is meant to run on applications that receive and interpret real-tim
 
     In a real production system, the [reward score](../concept-rewards.md) should be designed to align with your business objectives and KPIs. Determining how to calculate the reward metric may require some experimentation.
 
-Follow these steps to set up the Personalizer script.
+Open _personalizer-quickstart.js_ in a text editor or IDE and paste in the code below.
 
-1. Find your key and endpoint.
+:::code language="js" source="~/cognitive-services-quickstart-code/javascript/Personalizer/quickstart-sdk/personalizer-quickstart.js" id="snippet_1":::
 
-    [!INCLUDE [Personalizer find resource info](find-azure-resource-info.md)]
+## Code block 2: Iterate the learning loop
 
-1. Open _personalizer-quickstart.js_ in a text editor or IDE and paste in the code below.
+The next block of code defines the **main** method and closes out the script. It runs a learning loop iteration, in which it asks the user their preferences at the command line and sends that information to Personalizer to select the best action. It presents the selected action to the user, who makes a choice using the command-line. Then it sends a reward score to the Personalizer service to signal how well the service did in its selection.
 
-1. 1. Paste your key and endpoint into the code where indicated. Your endpoint has the form `https://<your_resource_name>.cognitiveservices.azure.com/`.
+The Personalizer learning loop is a cycle of **Rank** and **Reward** calls. In this quickstart, each Rank call, to personalize the content, is followed by a Reward call to tell Personalizer how well the service performed.
 
-    > [!IMPORTANT]
-    > Remember to remove the key from your code when you're done, and never post it publicly. For production, use a secure way of storing and accessing your credentials like [Azure Key Vault](../../../key-vault/general/overview.md). For more information about security, see the Cognitive Services [security](../../cognitive-services-security.md) article.
+1. Add the code below to _personalizer-quickstart.js_.
 
-    :::code language="js" source="~/cognitive-services-quickstart-code/javascript/Personalizer/quickstart-sdk/personalizer-quickstart.js" id="snippet_1":::
+1. Find your key and endpoint. Your endpoint has the form `https://<your_resource_name>.cognitiveservices.azure.com/`.
 
-## Code block 2: Iterate the learning loop
+    [!INCLUDE [Personalizer find resource info](find-azure-resource-info.md)]
 
-The next block of code defines the **main** method and closes out the script. It runs a learning loop iteration, in which it asks the user their preferences at the command line and sends that information to Personalizer to select the best action. It presents the selected action to the user, who makes a choice using the command-line. Then it sends a reward score to the Personalizer service to signal how well the service did in its selection.
+1. Paste your key and endpoint into the code where indicated.
 
-The Personalizer learning loop is a cycle of **Rank** and **Reward** calls. In this quickstart, each Rank call, to personalize the content, is followed by a Reward call to tell Personalizer how well the service performed.
+    > [!IMPORTANT]
+    > Remember to remove the key from your code when you're done, and never post it publicly. For production, use a secure way of storing and accessing your credentials like [Azure Key Vault](../../../key-vault/general/overview.md). For more information about security, see the Cognitive Services [security](../../cognitive-services-security.md) article.
 
-:::code language="js" source="~/cognitive-services-quickstart-code/javascript/Personalizer/quickstart-sdk/personalizer-quickstart.js" id="snippet_2":::
+    :::code language="js" source="~/cognitive-services-quickstart-code/javascript/Personalizer/quickstart-sdk/personalizer-quickstart.js" id="snippet_2":::
 
 ## Run the program