bymatlab· 88 skills
Deploy AI models to embedded hardware using MathWorks tools (MATLAB, Simulink, Embedded Coder). Covers two workflow patterns: (1) MathWorks-native or imported models rebuilt as dlnetwork for lean hardware, (2) direct C/C++ code generation from PyTorch and LiteRT models. Both patterns support all targets (Cortex-M/A/R, x86, GPU). Trigger when: user wants to deploy AI to embedded targets; generate C/CUDA from neural networks; compress AI models for MCU; integrate AI in Simulink for system-level simulation; import PyTorch/ONNX/TensorFlow models for embedded deployment; optimize AI for resource-constrained hardware; or use loadPyTorchExportedProgram, importNetworkFromPyTorch, dlquantizer, exportNetworkToSimulink, or Embedded Coder with AI models.
$npx -y skills add matlab/matlab-agentic-toolkit --skill matlab-deploy-embedded-aiInstalls into the current project.
Run `npx skills use "https://github.com/matlab/matlab-agentic-toolkit" --skill "matlab/matlab-agentic-toolkit/matlab-deploy-embedded-ai"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/matlab/matlab-agentic-toolkit" that are relevant to the current task. Run `npx skills add "https://github.com/matlab/matlab-agentic-toolkit"` and select the relevant skills, then follow their instructions.