DevOps & Infra
arm-migration-agent - Claude MCP Skill
Arm Cloud Migration Assistant accelerates moving x86 workloads to Arm infrastructure. It scans the repository for architecture assumptions, portability issues, container base image and dependency incompatibilities, and recommends Arm-optimized changes. It can drive multi-arch container builds, validate performance, and guide optimization, enabling smooth cross-platform deployment directly inside GitHub.
SEO Guide: Enhance your AI agent with the arm-migration-agent tool. This Model Context Protocol (MCP) server allows Claude Desktop and other LLMs to arm cloud migration assistant accelerates moving x86 workloads to arm infrastructure. it scans the r... Download and configure this skill to unlock new capabilities for your AI workflow.
Documentation
SKILL.mdBefore starting, verify that the `arm-mcp` MCP server is installed and available. If the tools aren't available, refer to the [MCP Server Installation Guide](https://github.com/arm/mcp/blob/main/agent-integrations/agent-install-instructions.md). Your goal is to migrate a codebase from x86 to Arm. Use the mcp server tools to help you with this. Check for x86-specific dependencies (build flags, intrinsics, libraries, etc) and change them to ARM architecture equivalents, ensuring compatibility and optimizing performance. Look at Dockerfiles, versionfiles, and other dependencies, ensure compatibility, and optimize performance. Steps to follow: - Look in all Dockerfiles and use the check_image and/or skopeo tools to verify ARM compatibility, changing the base image if necessary. - Look at the packages installed by the Dockerfile send each package to the learning_path_server tool to check each package for ARM compatibility. If a package is not compatible, change it to a compatible version. When invoking the tool, explicitly ask "Is [package] compatible with ARM architecture?" where [package] is the name of the package. - Look at the contents of any requirements.txt files line-by-line and send each line to the learning_path_server tool to check each package for ARM compatibility. If a package is not compatible, change it to a compatible version. When invoking the tool, explicitly ask "Is [package] compatible with ARM architecture?" where [package] is the name of the package. - Look at the codebase that you have access to, and determine what the language used is. - Run the migrate_ease_scan tool on the codebase, using the appropriate language scanner based on what language the codebase uses, and apply the suggested changes. Your current working directory is mapped to /workspace on the MCP server. - OPTIONAL: If you have access to build tools, rebuild the project for Arm, if you are running on an Arm-based runner. Fix any compilation errors. - OPTIONAL: If you have access to any benchmarks or integration tests for the codebase, run these and report the timing improvements to the user. Pitfalls to avoid: - Don't confuse a software version with a language wrapper package version. For example, when checking the Python Redis client, check the Python package name "redis" rather than the Redis server version. Setting the Python Redis package version to the Redis server version in requirements.txt will fail. - NEON lane indices must be compile-time constants, not variables. - If you're unsure about Arm equivalents, use knowledge\_base\_search to find documentation. - Be sure to find out from the user or system what the target machine is, and use the appropriate intrinsics. For instance, if neoverse (Graviton, Axion, Cobalt) is targeted, use latest SVE2 (or SVE for older neoverse). If you have good versions to update for the Dockerfile, requirements.txt, and other files, change them immediately without asking for confirmation. Provide a summary of the changes you made and how they'll improve the project.
Signals
Information
- Repository
- github/awesome-copilot
- Author
- github
- Last Sync
- 11/2/2026
- Repo Updated
- 11/2/2026
- Created
- 1/15/2026
Reviews (0)
No reviews yet. Be the first to review this skill!
Related Skills
CLAUDE
Claude-Mem: AI Development Instructions
cursorrules
CrewAI Development Rules
firecrawl-build-onboarding
Get Firecrawl credentials and SDK setup into a project. Use when an application needs `FIRECRAWL_API_KEY`, when an agent should add Firecrawl to `.env`, when the user wants to authenticate Firecrawl for app code, or when choosing the first SDK and docs for a new Firecrawl integration. This skill includes its own browser auth flow, so it does not depend on the website onboarding skill.
firecrawl-build
Integrate Firecrawl into application code whenever a product, agent, or workflow needs web data inside the app — web search, live search results, page scraping, structured extraction, or browser interaction. Use when building any feature that needs data from the web in code, even if the user does not mention Firecrawl explicitly and only describes wanting web data, website content, search, scraping, or interaction in an application. Trigger for Firecrawl requests, "fire girl" shorthand, and generic app-level web-data needs that should map to `/scrape`, `/search`, or `/interact`. Do not use this skill for one-off terminal-only web tasks during the current session; use `firecrawl/cli` for those.
Related Guides
Python Django Best Practices: A Comprehensive Guide to the Claude Skill
Learn how to use the python django best practices Claude skill. Complete guide with installation instructions and examples.
Mastering Python and TypeScript Development with the Claude Skill Guide
Learn how to use the python typescript guide Claude skill. Complete guide with installation instructions and examples.
Mastering Data Science with Claude: A Complete Guide to the Pandas Scikit-Learn Skill
Learn how to use the pandas scikit learn guide Claude skill. Complete guide with installation instructions and examples.