Production update

.wordlist.txt

@@ -5845,3 +5845,112 @@ reconnection
 stdin
 testcontainers
 ttyUSB
+ARMGCC
+ActiveGate
+Alif
+AlifSemiconductor
+Anymal
+Arranz
+Asier
+CHW
+Cartpole
+DK
+DTCM
+DevKit
+DevKit's
+Dynatrace
+Dynatrace's
+ELU
+ETE
+EthosUCompileSpec
+EthosUPartitioner
+EthosUQuantizer
+FOpenJDK
+Franka
+GAE
+IPPO
+ISAACSIM
+ITCM
+IsaacLab
+IsaacSim
+MAPPO
+MRAM
+MinSizeRel
+Mpeis
+MuJoCo
+NCHW
+NOBITS
+NVIC
+NVRTC
+Omniverse
+OneAgent
+OptimizingClang
+PBT
+PRG
+PROGBITS
+Paschalis
+Photorealistic
+PhysX
+Procedurally
+RDWR
+RELA
+RSL
+RTT
+RemoteProc
+SETOOLS
+SEUART
+SdkRootDirPath
+SimpleAdd
+TopDown
+TurboVNC
+URDF
+Unitree
+activegate
+alifsemi
+brbe
+bsort
+dockerfile
+dyn
+dynatrace
+envs
+exir
+f'Wrote
+ffunction
+fini
+flatbuffer
+heatmap
+icache
+isaac
+isaacsim
+libgomp
+lld
+mcuxpressotools
+mcuxsdk
+microcontroller's
+mobilenetv
+noinline
+nop
+omniverse
+orderfile
+preloading
+procedurally
+pybind
+quantizer
+randn
+readelf
+rela
+relocs
+relro
+remoteproc
+ro
+sb
+sdX
+skrl
+symlink
+syms
+toplevel
+uarch
+umount
+vtable
+xC
+Performix

assets/contributors.csv

@@ -97,7 +97,7 @@ Waheed Brown,Arm,https://github.com/armwaheed,https://www.linkedin.com/in/waheed
 Aryan Bhusari,Arm,,https://www.linkedin.com/in/aryanbhusari,,
 Ken Zhang,Insyde,,kai-di-zhang-b1642a266,,
 Ann Cheng,Arm,anncheng-arm,hello-ann,,
-Fidel Makatia Omusilibwa,,,,,
+Fidel Makatia Omusilibwa,,fidel-makatia,fidel-makatia-hsc-mieee,,
 Ker Liu,,,,,
 Rui Chang,,,,,
 Alejandro Martinez Vicente,Arm,,,,
@@ -113,5 +113,9 @@ Steve Suzuki,Arm,,,,
 Qixiang Xu,Arm,,,,
 Phalani Paladugu,Arm,phalani-paladugu,phalani-paladugu,,
 Richard Burton,Arm,Burton2000,,,
+Brendan Long,Arm,bccbrendan,https://www.linkedin.com/in/brendan-long-5817924/,,
 Asier Arranz,NVIDIA,,asierarranz,,asierarranz.com
-Prince Agyeman,Arm,,,,
+Prince Agyeman,Arm,,,,
+Parichay Das,,parichaydas,parichaydas,,
+Johnny Nunez,NVIDIA,johnnynunez,johnnycano,,
+Raymond Lo,NVIDIA,raymondlo84,raymondlo84,,

content/install-guides/codex-cli.md

@@ -233,6 +233,18 @@ The Arm MCP server is listed in the output. If the arm-mcp server indicates it's
 
 You can also verify the tools are available by asking Codex to list the available Arm MCP tools.
 
+### Use Arm prompt files with the MCP Server
+
+The Arm MCP Server provides a rich set of tools and knowledge base, but to make the best use of it, you should pair it with Arm-specific prompt files. These prompt files supply task-oriented context, best practices, and structured workflows that guide the agent in using MCP tools more effectively across common Arm development tasks.
+
+#### Get the prompt files
+
+Browse the [agent integrations directory for Codex](https://github.com/arm/mcp/tree/main/agent-integrations/codex) to find prompt files for specific use cases:
+
+- **Arm migration** ([arm-migration.md](https://github.com/arm/mcp/blob/main/agent-integrations/codex/arm-migration.md)): Helps the agent systematically migrate applications from x86 to Arm, including dependency analysis, compatibility checks, and optimization recommendations.
+
+Each prompt file is a Markdown configuration that you can reference in your Codex CLI sessions to enable more targeted, task-specific assistance.
+
 If you're facing issues or have questions, reach out to mcpserver@arm.com.
 
-You're now ready to use Codex CLI with Arm-specific development assistance.
+You're now ready to use Codex CLI with the Arm MCP server for Arm-specific development assistance.

content/install-guides/gemini.md

@@ -407,6 +407,18 @@ Configured MCP servers:
   - sysreport_instructions
 ```
 
+### Use Arm prompt files with the MCP Server
+
+The Arm MCP Server provides a rich set of tools and knowledge base, but to make the best use of it, you should pair it with Arm-specific prompt files. These prompt files supply task-oriented context, best practices, and structured workflows that guide the agent in using MCP tools more effectively across common Arm development tasks.
+
+#### Get the prompt files
+
+Browse the [agent integrations directory](https://github.com/arm/mcp/tree/main/agent-integrations/gemini) to find prompt files for specific use cases:
+
+- **Arm migration** ([arm-migration.toml](https://github.com/arm/mcp/blob/main/agent-integrations/gemini/arm-migration.toml)): Helps the agent systematically migrate applications from x86 to Arm, including dependency analysis, compatibility checks, and optimization recommendations.
+
+Each prompt file is a TOML configuration that you can reference in your Gemini CLI sessions to enable more targeted, task-specific assistance.
+
 If you're facing issues or have questions, reach out to mcpserver@arm.com.
 
-You're now ready to use Gemini CLI with the Arm MCP server for Arm-specific development assistance.
+You're now ready to use Gemini CLI with the Arm MCP server for Arm-specific development assistance.

content/install-guides/github-copilot.md

@@ -335,6 +335,20 @@ Example prompts that use the Arm MCP Server:
 - `Search the Arm knowledge base for Neon intrinsics examples`
 - `Find learning resources about migrating from x86 to Arm`
 
+## Use Arm prompt files with the MCP Server
+
+The Arm MCP Server provides a rich set of tools and knowledge base, but to make the best use of it, you should pair it with Arm-specific prompt files. These prompt files supply task-oriented context, best practices, and structured workflows that guide the agent in using MCP tools more effectively across common Arm development tasks.
+
+### Get the prompt files
+
+Browse the [agent integrations directory for Visual Studio Code](https://github.com/arm/mcp/tree/main/agent-integrations/vs-code) to find prompt files for specific use cases:
+
+- **Arm migration** ([arm-migration.prompt.md](https://github.com/arm/mcp/blob/main/agent-integrations/vs-code/arm-migration.prompt.md)): Helps the agent systematically migrate applications from x86 to Arm, including dependency analysis, compatibility checks, and optimization recommendations.
+
+Each prompt file is a Markdown configuration that you can reference in your GitHub Copilot sessions to enable more targeted, task-specific assistance.
+
+If you're facing issues or have questions, reach out to mcpserver@arm.com.
+
 ## Troubleshooting MCP Server connections
 
 This section helps you resolve common issues when installing and using GitHub Copilot with the Arm MCP Server on Arm systems. If you encounter problems not covered here, contact [mcpserver@arm.com](mailto:mcpserver@arm.com) for support.
@@ -349,4 +363,4 @@ If the Arm MCP Server doesn't connect:
 
 
 
-You're now ready to use GitHub Copilot with the Arm MCP Server to enhance your Arm development workflow!
+You're now ready to use GitHub Copilot with the Arm MCP server for Arm-specific development assistance.

content/install-guides/kiro-cli.md

@@ -262,6 +262,18 @@ Use the `/tools` command to list the available tools:
 
 You should see the Arm MCP server tools listed in the output. If the arm-mcp server says it's still loading, wait a moment and run `/tools` again.
 
-If you are facing issues or have questions, reach out to mcpserver@arm.com.
+### Use Arm prompt files with the MCP Server
 
-You're ready to use Kiro CLI.
+The Arm MCP Server provides a rich set of tools and knowledge base, but to make the best use of it, you should pair it with Arm-specific prompt files. These prompt files supply task-oriented context, best practices, and structured workflows that guide the agent in using MCP tools more effectively across common Arm development tasks.
+
+#### Get the prompt files
+
+Browse the [agent integrations directory for Kiro](https://github.com/arm/mcp/tree/main/agent-integrations/kiro) to find prompt files for specific use cases:
+
+- **Arm migration** ([arm-migration.md](https://github.com/arm/mcp/blob/main/agent-integrations/kiro/arm-migration.md)): Helps the agent systematically migrate applications from x86 to Arm, including dependency analysis, compatibility checks, and optimization recommendations.
+
+Each prompt file is a Markdown configuration that you can reference in your Kiro CLI sessions to enable more targeted, task-specific assistance.
+
+If you're facing issues or have questions, reach out to mcpserver@arm.com.
+
+You're now ready to use Kiro CLI with the Arm MCP server for Arm-specific development assistance.

content/install-guides/multipass.md

@@ -24,7 +24,7 @@ ecosystem_dashboard: https://developer.arm.com/ecosystem-dashboard/linux?package
 
 test_images:
 - ubuntu:latest
-test_maintenance: true
+test_maintenance: false
 
 ### PAGE SETUP
 weight: 1                       # Defines page ordering. Must be 1 for first (or only) page.

content/install-guides/perf.md

@@ -22,7 +22,7 @@ ecosystem_dashboard: https://developer.arm.com/ecosystem-dashboard/linux?package
 
 test_images:
 - ubuntu:latest
-test_maintenance: true
+test_maintenance: false
 
 ### PAGE SETUP
 weight: 1                       # Defines page ordering. Must be 1 for first (or only) page.

content/install-guides/pytorch.md

@@ -14,7 +14,7 @@ ecosystem_dashboard: https://developer.arm.com/ecosystem-dashboard/linux?package
 test_images:
 - ubuntu:latest
 test_link: null
-test_maintenance: true
+test_maintenance: false
 title: PyTorch
 tool_install: true
 weight: 1

content/learning-paths/automotive/_index.md

@@ -34,6 +34,7 @@ tools_software_languages_filter:
 - Raspberry Pi: 1
 - ROS 2: 3
 - Rust: 1
+- SME2: 1
 - Tinkerblox: 1
 - topdown-tool: 1
 - Zenoh: 1

content/learning-paths/automotive/openadkit1_container/1_sdv_soafee.md

@@ -8,15 +8,15 @@ layout: learningpathall
 
 ## Introduction to Software-Defined Vehicles
 
-In recent years, the automotive industry has been undergoing a transformation driven by software, with the concept of the Software-Defined Vehicle (SDV) emerging as a key paradigm for the future of intelligent cars. As the number of Electronic Control Units (ECUs) increases and vehicle systems become more complex, the traditional hardware-driven development approach is no longer sufficient. To improve development efficiency and product quality, automotive software development is moving to a Shift-Left approach, accelerating validation and deployment.
+In recent years, the automotive industry has been undergoing a transformation driven by software, with the concept of the Software-Defined Vehicle (SDV) emerging as a key paradigm for the future of intelligent cars. As Electronic Control Units (ECUs) increase and vehicle systems grow more complex, traditional hardware-driven development is no longer sufficient. To improve development efficiency and product quality, automotive software development is moving to a Shift-Left approach, accelerating validation and deployment.
 
 ## The evolution of Software-Defined Vehicles
 
 The core idea of SDV is to make software the primary differentiator in a vehicle, enabling continuous feature updates via Over-The-Air (OTA) technology. This approach allows manufacturers to shorten development cycles while continuously improving safety and performance after a vehicle is released. Moreover, SDV promotes the adoption of Service-Oriented Architecture (SOA), enabling modular and scalable software that integrates seamlessly with cloud services.
 
 However, this transition introduces new challenges, particularly in software development and validation. The traditional V-model development process struggles to meet SDV demands since defects are often detected late in development, leading to costly fixes. As a result, Shift-Left has become a crucial strategy to address these challenges.
 
-You can read more about [Software Defined Vehicles](https://www.arm.com/markets/automotive/software-defined-vehicles). 
+See [Software Defined Vehicles](https://www.arm.com/markets/automotive/software-defined-vehicles) for more information. 
 
 ## Shift-Left: detecting issues early to enhance development efficiency
 
@@ -32,7 +32,7 @@ The key benefits of Shift-Left include:
 
 However, Shift-Left requires appropriate tools and frameworks to support its implementation; otherwise, it can increase testing complexity. This is where SOAFEE (Scalable Open Architecture for Embedded Edge) plays a critical role.
 
-Read [Virtual Platforms from Arm and Partners Available Now to Accelerate and Transform Automotive Development](https://newsroom.arm.com/blog/automotive-virtual-platforms) to understand how virtual platforms enable the automotive industry to accelerate the silicon and software development process through virtual prototyping.
+See [Virtual Platforms from Arm and Partners Available Now to Accelerate and Transform Automotive Development](https://newsroom.arm.com/blog/automotive-virtual-platforms) for details on how virtual platforms enable the automotive industry to accelerate silicon and software development through virtual prototyping.
 
 ## SOAFEE: a standardized solution for SDV development
 
@@ -52,6 +52,8 @@ As the Software-Defined Vehicle paradigm gains traction, the automotive industry
 
 With the adoption of SOAFEE, automotive software development will become more standardized and efficient, enabling companies to realize the vision of SDVs faster while delivering a safer, smarter, and more flexible vehicle experience.
 
-Visit the [SOAFEE](https://www.soafee.io/) website to learn more.
+See the [SOAFEE](https://www.soafee.io/) website for additional resources.
 
-In the following sections, you will explore a Shift-Left demonstration example that leverages SOAFEE to enable early deployment of autonomous driving software before the hardware is ready.
+## What you've learned and what's next
+
+You now understand how Software-Defined Vehicles are transforming automotive development, and how SOAFEE and Shift-Left methodologies address the challenges of modern autonomous driving software development. In the next section, you'll learn about the specific technologies that enable this transformation: ROS 2 and Open AD Kit.

content/learning-paths/automotive/openadkit1_container/2_automotive_softwares.md

@@ -1,5 +1,5 @@
 ---
-title: Essential automotive software technologies
+title: Learn about ROS 2 and Open AD Kit
 weight: 3
 
 ### FIXED, DO NOT MODIFY
@@ -55,4 +55,6 @@ The Open AD Kit project continues to be developed by the Open AD Kit working gro
 
 The Open AD Kit Blueprint has been widely adopted by many ecosystem players to develop their own custom-flavored implementations. The blueprint provides a practical and demonstrable example of building SDV applications, particularly in the autonomous driving domain. Additionally, it serves as a model for creating SOAFEE blueprints, fostering a dynamic ecosystem around them.
 
-In the following sections, you will learn how to use the Open AD Kit autonomous driving simulation environment to run SOAFEE within a container and facilitate communication through ROS 2.
+## What you've learned and what's next
+
+You now understand how ROS 2 provides the foundation for autonomous driving middleware, and how Open AD Kit leverages this foundation to create a SOAFEE-compliant autonomous driving platform. In the next section, you'll set up Open AD Kit on an Arm Neoverse platform.

content/learning-paths/automotive/openadkit1_container/3_setup_openadkit.md

@@ -105,4 +105,6 @@ This command starts a new Docker container named `visualizer`, ensuring it runs
 docker run --name visualizer --rm -it -p 6080:6080 ghcr.io/autowarefoundation/demo-packages:visualizer
 ```
 
-After gaining a basic understanding of Open AD Kit, the next section will guide you through running three containers simultaneously on a single physical machine.
+## What you've learned and what's next
+
+You now understand the three core components of Open AD Kit (simulator, planning-control, and visualizer) and how they interact through ROS 2 topics. In the next section, you'll run all three containers together using Docker Compose to execute a complete autonomous driving simulation.

content/learning-paths/automotive/openadkit1_container/4_run_openadkit.md

@@ -150,7 +150,7 @@ Once the script starts successfully, you will see a similar output to the image
 
 You can use your browser to monitor the simulation data in real-time.
 
-![img1 alt-text#center](vnc_address.webp "Figure 1: Execute run.sh")
+![Terminal output showing the run.sh script execution with the VNC access URL displayed at the bottom, indicating the visualizer is ready for browser connection#center](vnc_address.webp "Terminal output showing run.sh execution with VNC URL")
 
 Now you can use the browser to access visualization.
 In this example the URL is http://34.244.98.151:6080/vnc.html
@@ -162,9 +162,9 @@ Ensure that the server allows your IP address and port 6080 to connect. You may
 To access the visualizer:
 1. Open a web browser and go to: `http://<server-ip>:6080/vnc.html`
 2. Click **Connect** on the VNC login screen.
-![img2 alt-text#center](openadkit_connect.jpg "Figure 2: Connect VNC")
+![VNC connection screen showing the Connect button that users click to establish the remote desktop connection to the Open AD Kit visualizer#center](openadkit_connect.jpg "VNC connection screen with Connect button")
 3. Enter the default VNC password: **"openadkit"**.
-![img3 alt-text#center](openadkit_passwd.jpg "Figure 3: Input VNC password")
+![VNC password prompt dialog requesting authentication, with an input field where users enter the default password 'openadkit' to access the visualization interface#center](openadkit_passwd.jpg "VNC password authentication dialog")
 
 You are now in the Open AD Kit simulation environment.
 
@@ -176,6 +176,6 @@ The vehicle starts from a stationary position, moves along the road, and stops w
 
 After each simulation run, it automatically restarts after 90 seconds. You can use the mouse to adjust different viewing angles for observation.
 
-![img4 alt-text#center](openadkit_1.gif "Figure 4: Simulation")
+![Animated simulation showing the autonomous vehicle navigating the road, stopping behind an obstacle, and in the second scenario changing lanes to pass around the obstruction, demonstrating Open AD Kit's planning and control capabilities#center](openadkit_1.gif "Open AD Kit simulation showing obstacle avoidance scenarios")
 
 Congratulations! You have successfully executed the Open AD Kit demo.

content/learning-paths/automotive/openadkit1_container/_index.md

@@ -1,18 +1,19 @@
 ---
 title: Deploy Open AD Kit containerized autonomous driving simulation on Arm Neoverse
+description: Learn how to deploy and run containerized autonomous driving simulations using Autoware Open AD Kit on Arm Neoverse with Docker, demonstrating SOAFEE-based Shift-Left development workflows.
 
 minutes_to_complete: 60
 
 who_is_this_for: This is an introductory topic for automotive developers, aimed at helping them accelerate autonomous driving software development before automotive hardware is available.
 
 learning_objectives: 
-    - Understand the SOAFEE architecture and its role in supporting Shift-Left software development strategies to optimize the autonomous driving development process.
-    - Use the Autoware Open AD Kit simulation environment.
-    - Run containerized workloads on Arm Neoverse processors with Docker, supporting execution on both cloud-based and on-premise servers.
-    - Explore advanced configurations and future development prospects.
+    - Understand the SOAFEE architecture and its role in supporting Shift-Left software development strategies to optimize the autonomous driving development process
+    - Use the Autoware Open AD Kit simulation environment
+    - Run containerized workloads on Arm Neoverse processors with Docker, supporting execution on both cloud-based and on-premise servers
+    - Explore advanced configurations and future development prospects
 prerequisites:
-    - An Arm Neoverse cloud instance, or a local Arm Neoverse Linux computer with at least 16 CPUs and 32GB of RAM.
-    - Familiarity with Docker and Docker Compose.
+    - An Arm Neoverse cloud instance, or a local Arm Neoverse Linux computer with at least 16 CPUs and 32GB of RAM
+    - Familiarity with Docker and Docker Compose
 
 author: Odin Shen