contractions and style updates

Author: anupras-mohapatra-arm

content/learning-paths/mobile-graphics-and-gaming/ams/ams.md

@@ -30,7 +30,7 @@ For installation instructions, see the [Arm Performance Studio install guide](/i
 
 ## Update your PATH environment variable (Linux and macOS)
 
-Edit your `PATH` environment variable to add the paths to the Streamline and Mali Offline Compiler executables. By adding the paths, you can run Streamline's `Streamline-cli -pa` command and Mali Offline Compiler's `malioc` command from any directory. This step is not necessary on Windows, as this is done automatically when Arm Performance Studio is installed.
+Edit your `PATH` environment variable to add the paths to the Streamline and Mali Offline Compiler executables. By adding the paths, you can run Streamline's `Streamline-cli -pa` command and Mali Offline Compiler's `malioc` command from any directory. This step isn't necessary on Windows, as this is done automatically when Arm Performance Studio is installed.
 
 On macOS, edit your `/etc/paths` file to add the following paths:
 

content/learning-paths/mobile-graphics-and-gaming/ams/fa.md

@@ -76,7 +76,7 @@ Explore each frame to evaluate how efficiently they were rendered on the device.
 
     ![Content Metrics view in Frame Advisor sorted by primitive count with the Prims column highlighted to identify expensive draw calls#center](images/fa_content_metrics.png)
 
-4. For an expensive object, check the **Detailed Metrics** view to see how efficiently the object's mesh is being rendered to the screen. Look for objects with duplicated vertices, or those that do not efficiently reuse indices.
+4. For an expensive object, check the **Detailed Metrics** view to see how efficiently the object's mesh is being rendered to the screen. Look for objects with duplicated vertices, or those that don't efficiently reuse indices.
 
     ![Detailed Metrics view in Frame Advisor showing mesh complexity, locality, redundancy, and memory layout for the selected draw call#center](images/fa_detailed_metrics_view.png)
 

content/learning-paths/mobile-graphics-and-gaming/ams/malioc.md

@@ -42,7 +42,7 @@ malioc --info --core <GPU_name>
 
 You can compile OpenGL ES (`--opengles`) and Vulkan (`--vulkan`) shader programs. On Linux hosts, you can also compile OpenGL (`--opengl <version>`) C kernels.
 
-A performance report will be generated.
+Mali Offline Compiler generates a performance report.
 
 If your frame analysis points to shader cost, compile one of your shaders. You can also use this sample shader to learn how to read the report. 
 
@@ -89,7 +89,7 @@ For more information, see [Compiling OpenGL ES shaders](https://developer.arm.co
 
 ## Interpret the report
 
-The report will provide an approximate cycle cost breakdown for the major functional units in the design. Use this information to optimize your shader.
+The report provides an approximate cycle cost breakdown for the major functional units in the design. Use this information to optimize your shader.
 
 For example, compiling the unoptimized implementation for `Mali-G76` reports the following cycle information:
 ```output

content/learning-paths/mobile-graphics-and-gaming/ams/pa.md

@@ -12,7 +12,7 @@ layout: "learningpathall"
 
 ## Connect to Android device and collect frame data
 
-Now that you have seen a [Performance Advisor example report](/learning-paths/mobile-graphics-and-gaming/ams/pa_example/), you can use it to capture data from your own application.
+Now that you've seen a [Performance Advisor example report](/learning-paths/mobile-graphics-and-gaming/ams/pa_example/), you can use it to capture data from your own application.
 
 Performance Advisor runs on a Streamline capture file, so the first step is to take a capture with Streamline. Streamline must capture extra frame data from the device, which Performance Advisor needs to generate a report. To capture the extra frame data, you must first run the provided Python script, `streamline_me.py`.
 
@@ -79,7 +79,7 @@ For full instructions, see the [Get started with Performance Advisor Tutorial](h
 
 3. The application starts automatically on the device. Interact with the application as required.
 
-4. When you have collected enough data, select **Stop capture**.
+4. When you've collected enough data, select **Stop capture**.
 
 5. Return to your terminal, and press `ENTER` to terminate the `streamline_me.py` script.
 
@@ -118,7 +118,7 @@ This feature is particularly useful when used within a [CI workflow](https://dev
 
 ## Specify performance budgets
 
-You can specify a performance budget which will be reflected in the Performance Advisor report. For more information, see [Setting performance budgets](https://developer.arm.com/documentation/102009/latest/Quick-start-guide/Setting-performance-budgets) in the Arm documentation.
+You can specify a performance budget that is reflected in the Performance Advisor report. For more information, see [Setting performance budgets](https://developer.arm.com/documentation/102009/latest/Quick-start-guide/Setting-performance-budgets) in the Arm documentation.
 
 ## What you've accomplished and what's next
 

content/learning-paths/mobile-graphics-and-gaming/ams/renderdoc.md

@@ -24,7 +24,7 @@ To run RenderDoc for Arm GPUs:
 
    The RenderDoc APK starts running on your target.
 
-   If you don't see your device, check that your device is setup correctly as described in [Setup tasks](/learning-paths/mobile-graphics-and-gaming/ams/setup_tasks/).
+   If you don't see your device, check that your device is set up correctly as described in [Setup tasks](/learning-paths/mobile-graphics-and-gaming/ams/setup_tasks/).
 
 2. Navigate to the **Launch Application** tab, and set the **Executable Path** to the application that you want to debug. Select the **Browse** button to view all of the installed application packages on the target and find the `.exe` file.
 
@@ -40,9 +40,9 @@ To run RenderDoc for Arm GPUs:
 
     Use these controls to take captures of your application as it runs on the target device. Captured frames are stored temporarily on the device.
 
-4. When you have finished capturing the frames of interest, stop the application that you are debugging. Keep RenderDoc running so that you can analyze and debug your captures.
+4. When you've finished capturing the frames of interest, stop the application that you are debugging. Keep RenderDoc running so that you can analyze and debug your captures.
 
-5. Select a capture from the **Captures collected** window and select **Open**. When the frame has loaded, it is displayed on the target and in the **Texture Viewer** tab, and the **Event Browser** is populated.
+5. Select a capture from the **Captures collected** window and select **Open**. When the frame has loaded, it's displayed on the target and in the **Texture Viewer** tab, and the **Event Browser** is populated.
 
     ![Screenshot of a captured frame opened in RenderDoc showing the Event Browser, Texture Viewer, API Inspector, and output preview for the selected event#center](images/rd_full_ui.png)
 

content/learning-paths/mobile-graphics-and-gaming/ams/setup_tasks.md

@@ -1,6 +1,6 @@
 ---
 # User change
-title: Set up an Android application
+title: Set up an Android application for profiling
 
 description: Prepare a debuggable Android application and device connection so Arm Performance Studio can capture profiling data.
 
@@ -22,7 +22,7 @@ Compile the application with debug enabled, as well as additional options to fac
 
 - To set [Unity](https://unity.com/) applications to be debuggable, enable **[Development Build](https://docs.unity3d.com/6000.0/Documentation/Manual/android-BuildProcess.html)** in **Build settings**.
 - In Android Studio, use a build variant that includes `debuggable true` (`isDebuggable = true` in Kotlin scripts) in the build configuration.
-- In Unreal Engine, open **Project Settings > Project > Packaging > Project**, and ensure that the **For Distribution** checkbox is not set.
+- In Unreal Engine, open **Project Settings > Project > Packaging > Project**, and ensure that the **For Distribution** checkbox isn't set.
 - For instructions to compile your C++ or Java applications with the right options, see the [Target setup guide for Android](https://developer.arm.com/documentation/101813/latest/Target-Setup/Compile-your-application).
 
 {{% notice Tip %}}

content/learning-paths/mobile-graphics-and-gaming/ams/streamline.md

@@ -12,7 +12,7 @@ layout: "learningpathall"
 
 ## Select the device and application in Streamline
 
-Now that you have seen an [Arm Streamline example capture](/learning-paths/mobile-graphics-and-gaming/ams/streamline_example/), you can use it to capture data from your own application.
+Now that you've seen an [Arm Streamline example capture](/learning-paths/mobile-graphics-and-gaming/ams/streamline_example/), you can use it to capture data from your own application.
 
 1. Launch the Performance Studio Hub and open Streamline.
 
@@ -29,19 +29,19 @@ Now that you have seen an [Arm Streamline example capture](/learning-paths/mobil
     ![Screenshot of the Streamline Start view with Android adb selected, a connected Samsung device selected, a debuggable application selected, and Capture Arm GPU profile enabled#center](images/start.png "Connect to the device")
 
 {{% notice Tip %}}
-Optionally, you can set a preferred location to store your captures using **Window** > **Preferences** > **Data Locations**. New reports will be created in the topmost folder specified.
+Optionally, you can set a preferred location to store your captures using **Window** > **Preferences** > **Data Locations**. New reports are created in the topmost folder specified.
 {{% /notice %}}
 
 ## Capture data
 
 1. Select **Start capture** to start capturing profile data from the device. Enter a name and location for the capture file.
 
-2. The application starts automatically on the device. Interact with the application as desired for the profiling run you wish to do.
+2. The application starts automatically on the device. Interact with the application as desired for the profiling run you want to do.
 
-3. When you have collected enough data, select **Stop capture**.
+3. When you've collected enough data, select **Stop capture**.
 ![Screenshot of Streamline during a capture with the Stop capture button highlighted and performance charts updating in the Timeline view#center](images/stop_capture.webp "Stop Capture")
 
-Streamline will stop capturing data, remove the daemon, and process the captured data.
+Streamline stops capturing data, removes the daemon, and processes the captured data.
 
 ## Analyze the results