MicrosoftDocs · openpublishbuild · Nov 24, 2020 · Nov 24, 2020 · Nov 25, 2020 · Nov 25, 2020
diff --git a/.openpublishing.publish.config.json b/.openpublishing.publish.config.json
@@ -1,4 +1,5 @@
 {
+  "xref_query_tags": ["/dotnet", "/uwp/api"],
   "docsets_to_publish": [
     {
       "docset_name": "bot-framework",
@@ -37,35 +38,6 @@
       "build_entry_point": "docs",
       "template_folder": "_themes",
       "version": 0
-    },
-    {
-      "docset_name": "bot-framework-dotnet-api",
-      "build_source_folder": "dotnet",
-      "build_output_subfolder": "bot-framework-dotnet-api",
-      "locale": "en-us",
-      "open_to_public_contributors": true,
-      "type_mapping": {
-        "Conceptual": "Content",
-        "ManagedReference": "Content",
-        "RestApi": "Content",
-        "NetEnum": "Content",
-        "NetDelegate": "Content",
-        "NetNamespace": "Content",
-        "NetMember": "Content",
-        "NetType": "Content"
-      },
-      "build_entry_point": "docs",
-      "template_folder": "_themes",
-      "customized_tasks": {
-        "docset_postbuild": [
-          "_dependentPackages/ECMA2Yaml/tools/PostBuild.ps1"
-        ],
-        "docset_prebuild": [
-          "_dependentPackages/ECMA2Yaml/tools/Run.ps1",
-          "_dependentPackages/CommonPlugins/tools/SplitTOC.ps1",
-          "_dependentPackages/CommonPlugins/tools/DiffFolder.ps1"
-        ]
-      }
     }
   ],
   "notification_subscribers": [
@@ -86,6 +58,11 @@
       "branch": "master",
       "branch_mapping": {}
     },
+    {
+      "path_to_root": "_themes.pdf",
+      "url": "https://github.com/Microsoft/templates.docs.msft.pdf",
+      "branch": "master"
+    },
     {
       "path_to_root": "botbuilder-samples",
       "url": "https://github.com/Microsoft/BotBuilder-Samples",
@@ -132,18 +109,6 @@
       "version": "latest"
     }
   ],
-  "ECMA2Yaml": {
-    "SourceXmlFolder": "dotnet/xml",
-    "OutputYamlFolder": "dotnet/api",
-    "Flatten": true,
-    "SDPMode": true
-  },
-  "DiffFolder": [
-    "dotnet/api"
-  ],
-  "SplitTOC": [
-    "dotnet/api/toc.yml"
-  ],
   "docs_build_engine": {
     "name": "docfx_v3"
   }

diff --git a/.openpublishing.redirection.json b/.openpublishing.redirection.json
@@ -2082,6 +2082,11 @@
       "redirect_url": "api/conversations",
       "redirect_document_id": false
     },
+    {
+      "source_path": "articles/v4sdk/bot-builder-dialogs-greeting.md",
+      "redirect_url": "/azure/bot-service/bot-builder-send-welcome-message",
+      "redirect_document_id": false
+    },
     {
       "source_path": "articles/v4sdk/bot-builder-tutorial-basic-deploy.md",
       "redirect_url": "/azure/bot-service/bot-builder-tutorial-create-basic-bot",

diff --git a/articles/TOC.yml b/articles/TOC.yml
@@ -250,6 +250,8 @@
       href: bot-service-debug-inspection-middleware.md
     - name: Debug your bot using transcript files
       href: v4sdk/bot-builder-debug-transcript.md
+    - name: Debug your bot with Adaptive Tools
+      href: bot-service-debug-adaptive-tools.md
   - name: Deploy
     items:
     - name: Deploy your bot to Azure
@@ -295,7 +297,7 @@
             href: bot-service-channel-directline-extension-net-client.md
           - name: Use extension with WebChat
             href: bot-service-channel-directline-extension-webchat-client.md
-          - name: Use extenson within VNET
+          - name: Use extension within VNET
             href: bot-service-channel-directline-extension-vnet.md
       - name: Alexa
         href: bot-service-channel-connect-alexa.md

diff --git a/articles/adaptive-dialog/adaptive-dialog-prebuilt-inputs.md b/articles/adaptive-dialog/adaptive-dialog-prebuilt-inputs.md
@@ -260,7 +260,7 @@ var ConfirmationDialog = new AdaptiveDialog("ConfirmationDialog") {
                     // text is read from a specific memory location. The caller of this dialog needs to
                     // set the prompt string to that location before calling the "ConfirmationDialog".
                     // All prompts support rich language generation based resolution for output generation.
-                    // See https://aka.ms/language-generation-file-format to learn more about the LG
+                    // See https://docs.microsoft.com/azure/bot-service/file-format/bot-builder-lg-file-format to learn more about the LG
                     // template format used in the ActivityTemplate object.
                     Prompt = new ActivityTemplate("${turn.contoso.travelBot.confirmPromptMessage}")
                 }
@@ -590,8 +590,8 @@ The following links provide generalized information on the topic of authenticati
 * [Add authentication to a bot][add-authentication]
 
 <!-- links -->
-[authentication]:https://aka.ms/azure-bot-authentication
-[add-authentication]:https://aka.ms/azure-bot-add-authentication
+[authentication]:../v4sdk/bot-builder-concept-authentication.md
+[add-authentication]:../v4sdk/bot-builder-authentication.md
 [recognizers]:../v4sdk/bot-builder-concept-adaptive-dialog-recognizers.md
 [adaptive-expressions]:../v4sdk/bot-builder-concept-adaptive-expressions.md
 [interruptions]: ../v4sdk/bot-builder-concept-adaptive-dialog-interruptions.md
diff --git a/articles/adaptive-dialog/adaptive-dialog-prebuilt-recognizers.md b/articles/adaptive-dialog/adaptive-dialog-prebuilt-recognizers.md
@@ -284,11 +284,11 @@ var adaptiveDialog = new AdaptiveDialog()
 
 ### Cross training your LUIS and QnA models
 
-To gain the full benefits of the cross-trained recognizer set, [cross train][cross-train-concepts] your `.lu` and `.qna` files. The Bot Framework Command Line Interface (BF CLI) tool provides a command to automate this process, the [luis:cross-train][bf-luiscross-train] and [qnamaker:cross-train][qnamaker-cross-train] commands. Running the cross-train command will create copies of the `.lu` and `.qna` files, make the required updates, then save to the specified directory.
+To gain the full benefits of the cross-trained recognizer set, [cross train][cross-train-concepts] your .lu and .qna files. The Bot Framework Command Line Interface (BF CLI) tool provides a command to automate this process, the [luis:cross-train][bf-luiscross-train] and [qnamaker:cross-train][qnamaker-cross-train] commands. Running the cross-train command will create copies of the .lu and .qna files, make the required updates, then save to the specified directory.
 
 > [!TIP]
 >
-> To create the cross-trained files, both `.lu`  and `.qna`, you can use _either_ the BF CLI `luis:cross-train` or `qnamaker:cross-train` command. You do not need to run both commands since they both do the same thing. The following demonstrates using the `luis:cross-train` command:
+> To create the cross-trained files, both .lu  and .qna, you can use _either_ the BF CLI `luis:cross-train` or `qnamaker:cross-train` command. You do not need to run both commands since they both do the same thing. The following demonstrates using the `luis:cross-train` command:
 
 ``` cli
 bf luis:cross-train -i <input-folder-name> -o <output-file-name> --config <cross-train-configuration-file>
@@ -298,9 +298,9 @@ For an end to end example of cross training your bot, see how to [Create a bot c
 
 ### luis:cross-train required parameters
 
-- `--in`: The directory, including sub-directories, that will be searched for both `.lu` and `.qna` files.
-- `--out`: The directory that the new cross-trained `.lu` and `.qna` output files will be saved to. This is the directory to which you will point the `luis:build` command's `--in` option.
-- `--config`: This points to the cross-train configuration file, a JSON file that is necessary for the command to work. 
+- `--in`: The directory, including sub-directories, that will be searched for both .lu and .qna files.
+- `--out`: The directory that the new cross-trained .lu and .qna output files will be saved to. This is the directory to which you will point the `luis:build` command's `--in` option.
+- `--config`: This points to the cross-train configuration file, a JSON file that is necessary for the command to work.
 
 #### The cross-train configuration file
 
@@ -335,7 +335,7 @@ The following is the general structure of a cross-train configuration file.
 }
 ```
 
-In the triggers section of the cross-train configuration file, list each intent in the root dialog along with the `.lu` file it points to. You only need to list the `.lu` files, `.qna` files will be cross trained as long as they are in the same directory with the same filename, for example _AddToDoDialog.qna_.
+In the triggers section of the cross-train configuration file, list each intent in the root dialog along with the .lu file it points to. You only need to list the .lu files, .qna files will be cross trained as long as they are in the same directory with the same filename, for example _AddToDoDialog.qna_.
 
 For example, a bot with the following dialog structure:
 
@@ -429,16 +429,16 @@ If language is included, the example config should be like this:
 
 <!-- Footnote-style links -->
 [1]:../v4sdk/bot-builder-concept-adaptive-dialog-generators.md
-[2]:https://aka.ms/regular-expression-language-reference
+[2]:/dotnet/standard/base-types/regular-expression-language-quick-reference
 [3]:https://github.com/microsoft/botbuilder/blob/master/specs/botframework-activity/botframework-activity.md#locale
 [4]:https://luis.ai
-[5]:https://aka.ms/luis-what-is-luis
-[6]:https://aka.ms/botbuilder-luis-concept?view=azure-bot-service-4.0
+[5]:/azure/cognitive-services/luis/what-is-luis
+[6]:../v4sdk/bot-builder-concept-luis.md
 [7]:../file-format/bot-builder-lu-file-format.md
 [8]:../v4sdk/bot-builder-concept-adaptive-expressions.md
-[9]:https://aka.ms/luis-concept-data-extraction?tabs=v2
-[10]:https://aka.ms/bot-service-add-luis-to-bot
-[11]:https://aka.ms/luis-create-new-app-in-luis-portal
+[9]:/azure/cognitive-services/luis/luis-concept-data-extraction?tabs=V2
+[10]:../v4sdk/bot-builder-howto-v4-luis.md
+[11]:/azure/cognitive-services/luis/luis-how-to-start-new-app
 [12]:https://qnamaker.ai
 [13]:https://azure.microsoft.com/services/cognitive-services/
 [cross-train-concepts]: ../v4sdk/bot-builder-concept-cross-train.md

diff --git a/articles/adaptive-dialog/adaptive-dialog-prebuilt-triggers.md b/articles/adaptive-dialog/adaptive-dialog-prebuilt-triggers.md
@@ -37,14 +37,17 @@ Triggers = new List<OnCondition>()
 |QnAMatch intent|`OnQnAMatch`| `RecognizedIntent` |This trigger is run when the [QnAMakerRecognizer][qna-maker-recognizer] has returned a `QnAMatch` intent. The entity `@answer` will have the `QnAMaker` answer.|
 |Unknown intent recognized| `OnUnknownIntent` | `UnknownIntent` | Actions to perform when user input is unrecognized or no match is found in any of the `OnIntent` triggers. You can also use this as your first trigger in your root dialog in place of the `OnBeginDialog` to preform any needed tasks when the dialog first starts. |
 
+> [!TIP]
+> Use the `OnUnknownIntent` trigger to catch and respond when a "none" intent occurs. Using the `OnIntent` trigger to handle a "none" intent can produce unexpected results.
+
 ### Recognizer event example
 
 Examples of `OnIntent` and `OnUnknownIntent` triggers are given in the example below to demonstrate the use of the Recognizer triggers.
 
 > [!NOTE]
 >
 > - The `OnIntent` trigger lets you handle the `recognizedIntent` event. The `recognizedIntent` event is raised by a [recognizer][recognizers]. With the exception of the [QnA Maker recognizer][qna-maker-recognizer], all of the Bot Framework SDK built-in recognizers emit this event when they successfully identify a user _input_ so that your bot can respond appropriately.
-> - Use the `OnUnknownIntent` trigger to catch and respond when a `recognizedIntent` event isn't caught and handled by any of the other triggers. This means that any unhandled intent (including "none") can cause it to trigger. But only if there aren't any currently executing actions for the dialog. <!--This is especially helpful to capture and handle cases where your dialog wishes to participate in consultation.-->
+> - Use the `OnUnknownIntent` trigger to catch and respond when a `recognizedIntent` event isn't caught and handled by any of the other triggers. This means that any unhandled intent (including "none") can cause it to trigger, but only if there aren't any currently executing actions for the dialog.<!--Use the `OnUnknownIntent` trigger to catch and respond when a "none" intent occurs. This is especially helpful to capture and handle cases where your dialog wishes to participate in consultation.-->
 
 ``` C#
 // Create the root dialog as an Adaptive dialog.

diff --git a/articles/bot-service-adapter-connect-webex.md b/articles/bot-service-adapter-connect-webex.md
@@ -47,7 +47,7 @@ Before you can complete the configuration of our Webex app, you need to wire up
 
 ### Install the Webex adapter NuGet package
 
-Add  the [Microsoft.Bot.Builder.Adapters.Webex](https://www.nuget.org/packages/Microsoft.Bot.Builder.Adapters.Webex/) NuGet package. For more information on using NuGet, see [Install and manage packages in Visual Studio](https://aka.ms/install-manage-packages-vs)
+Add  the [Microsoft.Bot.Builder.Adapters.Webex](https://www.nuget.org/packages/Microsoft.Bot.Builder.Adapters.Webex/) NuGet package. For more information on using NuGet, see [Install and manage packages in Visual Studio](/nuget/tools/package-manager-ui)
 
 ### Create a Webex adapter class
 
@@ -89,7 +89,7 @@ Once added, your ***ConfigureServices*** method should look like this.
 
 Now that you have created a Webex app and wired up the adapter in your bot project, the final steps are to configure a Webex webhook, point it to the correct endpoint on your bot, and subscribe your app to ensure your bot receives messages and attachments. To do this your bot must be running, so that Webex can verify the URL to the endpoint is valid.
 
-1. To complete this step, [deploy your bot to Azure](https://aka.ms/bot-builder-deploy-az-cli) and make a note of the URL to your deployed bot. Your Webex messaging endpoint is the URL for your bot, which will be the URL of your deployed application (or ngrok endpoint), plus '/api/webex' (for example, `https://yourbotapp.azurewebsites.net/api/webex`).
+1. To complete this step, [deploy your bot to Azure](./bot-builder-deploy-az-cli.md) and make a note of the URL to your deployed bot. Your Webex messaging endpoint is the URL for your bot, which will be the URL of your deployed application (or ngrok endpoint), plus '/api/webex' (for example, `https://yourbotapp.azurewebsites.net/api/webex`).
 
     > [!NOTE]
     > If you are not ready to deploy your bot to Azure, or wish to debug your bot when using the Webex adapter, you can use a tool such as [ngrok](https://www.ngrok.com) (which you will likely already have installed if you have used the Bot Framework Emulator previously) to tunnel through to your bot running locally and provide you with a publicly accessible URL for this.

diff --git a/articles/bot-service-build-continuous-deployment.md b/articles/bot-service-build-continuous-deployment.md
@@ -38,7 +38,7 @@ To enable continuous deployment with GitHub, navigate to the **App Service** pag
 
 1. Click **Deployment Center** > **GitHub** > **Authorize**.
 
-   ![Continous deployment](~/media/azure-bot-build/azure-deployment.png)
+   ![Continuos deployment](~/media/azure-bot-build/azure-deployment.png)
 
    1. In the browser window that opens up, click **Authorize AzureAppService**.
 

diff --git a/articles/bot-service-channel-connect-cortana.md b/articles/bot-service-channel-connect-cortana.md
@@ -110,10 +110,10 @@ Next, you need to enable and authorize the Bot skill to connect to your account.
 
 ## Next steps
 
-* [Cortana Skills Kit](https://aka.ms/CortanaSkillsKitOverview)
+* [Cortana Skills Kit](/cortana/skills/overview)
 * [Enable debugging](bot-service-debug-cortana-skill.md)
 * [Publish a Cortana skill][publish]
 
 [invocation]: https://docs.microsoft.com/cortana/skills/cortana-invocation-guidelines
 [publish]: https://docs.microsoft.com/cortana/skills/publish-skill
-[CortanaEntity]: https://aka.ms/cortana-channel-data
+[CortanaEntity]: /cortana/skills/cortana-channel-data
diff --git a/articles/bot-service-channel-connect-directline.md b/articles/bot-service-channel-connect-directline.md
@@ -17,7 +17,6 @@ This article describes how to connect a bot to the **Direct Line channel**. Use
 > NOTE
 > The Direct Line is a standard channel over HTTPS protocol to allow communication between a client application and a bot. If you require network isolation instead, use the [Direct Line App Service Extension](bot-service-channel-directline-extension.md) over [WebSocket protocol](https://tools.ietf.org/html/rfc6455).
 
-
 ## Add the Direct Line channel
 
 The first thing you must do is to add the Direct Line channel to the bot.
@@ -110,7 +109,7 @@ The example contains two projects:
     </appSettings>
     ```
 
-User messages are sent to the Bot using the Direct Line Client `Conversations.PostActivityAsync` method using the `ConversationId` generated previously.
+User messages are sent to the bot using the Direct Line Client `Conversations.PostActivityAsync` method using the `ConversationId` generated previously.
 
 ```csharp
 while (true)

diff --git a/articles/bot-service-channel-connect-directlinespeech.md b/articles/bot-service-channel-connect-directlinespeech.md
@@ -17,7 +17,7 @@ ms.author: v-mimiel
 
 This article describes how to connect a bot to the **Direct Line Speech channel**. Use this channel to allow users to interact with a bot via voice.
 
-Once you have built your bot, onboarding it with Direct Line Speech will enable low latency, high reliability connection with client applications using the [Speech SDK](https://aka.ms/speech-service-docs). These connections are optimized for voice in, voice out conversational experiences. For more information on Direct Line Speech and how to build client applications, visit the [custom voice-first virtual assistant](https://aka.ms/cognitive-services-voice-assistants) page.
+Once you have built your bot, onboarding it with Direct Line Speech will enable low latency, high reliability connection with client applications using the [Speech SDK](/azure/cognitive-services/speech-service/). These connections are optimized for voice in, voice out conversational experiences. For more information on Direct Line Speech and how to build client applications, visit the [custom voice-first virtual assistant](/azure/cognitive-services/Speech-Service/voice-assistants) page.
 
 ## Prerequisites
 
@@ -77,7 +77,7 @@ With the Direct Line Speech channel connected to your bot, you now need to enabl
 
 1. Click `Save` at the top of the configuration page.
 
-1. The Bot Framework Protocol Streaming Extensions are now enabled for your bot. You are now ready to update your bot code and [integrate Streaming Extensions support](https://aka.ms/botframework/addstreamingprotocolsupport) to an existing bot project.
+1. The Bot Framework Protocol Streaming Extensions are now enabled for your bot. You are now ready to update your bot code and [integrate Streaming Extensions support](directline-speech-bot.md) to an existing bot project.
 
 ## Example
 
@@ -92,4 +92,4 @@ The following picture shows the client application interface when communicating
 > [!NOTE]
 > The following step is only needed for bots built before the release of the 4.8 SDKs.
 
-With the Direct Line Speech channel connected and support for the Bot Framework Protocol Streaming Extensions enabled, all that's left is to add code to your bot to support the optimized communication. Follow the instructions on [adding Streaming Extensions support to your bot](https://aka.ms/botframework/addstreamingprotocolsupport) to ensure full compatibility with Direct Line Speech.
+With the Direct Line Speech channel connected and support for the Bot Framework Protocol Streaming Extensions enabled, all that's left is to add code to your bot to support the optimized communication. Follow the instructions on [adding Streaming Extensions support to your bot](directline-speech-bot.md) to ensure full compatibility with Direct Line Speech.