This skill provides comprehensive guidelines for optimizing MATLAB code performance. It's aimed at developers and engineers looking to enhance their MATLAB applications through vectorization, memory optimization, and profiling tools.
$ npx skills add https://github.com/matlab/skills --skill matlab-performance-optimizerThis skill provides guidelines for optimizing MATLAB code performance using vectorization, memory optimization, and profiling tools. It helps developers and engineers identify performance bottlenecks and implement best practices to enhance application efficiency. The skill works with AI coding agents to guide optimization decisions throughout the development process. It addresses common performance challenges in MATLAB applications by leveraging built-in profiling and analysis tools. This resource is useful for teams looking to improve computational speed and reduce memory consumption in their MATLAB projects.
Install using npm with the command: `$ npx skills add https://github.com/matlab/skills --skill matlab-performance-optimizer`
Optimizing slow or inefficient MATLAB code
Converting loops to vectorized operations
Reducing memory usage
Improving algorithm performance
$ npx skills add https://github.com/matlab/skills --skill matlab-performance-optimizergit clone https://github.com/matlab/skillsCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Check the GitHub repository or documentation for usage examples.
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