Matlab Deploy Embedded AI
majiayu000/claude-skill-registry
Deploy AI models to embedded hardware using MathWorks tools (MATLAB, Simulink, Embedded Coder).
Deploy AI models to embedded hardware using MathWorks tools (MATLAB, Simulink, Embedded Coder).
Install Embedded AI Deployment
$ npx skills add matlab/agent-skills-playground --skill embedded-ai-deployment -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install matlab/agent-skills-playground embedded-ai-deployment --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/matlab/agent-skills-playground.git skills-src && mkdir -p .claude/skills && cp -r skills-src/demos/embedded-ai-deployment/skills/embedded-ai-deployment .claude/skills/embedded-ai-deployment && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "embedded-ai-deployment" agent skill from https://github.com/matlab/agent-skills-playground/tree/main/demos/embedded-ai-deployment/skills/embedded-ai-deployment into .claude/skills/embedded-ai-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "embedded-ai-deployment", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/matlab/agent-skills-playground/tree/main/demos/embedded-ai-deployment/skills/embedded-ai-deploymentType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add matlab/agent-skills-playground --skill embedded-ai-deployment -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install matlab/agent-skills-playground embedded-ai-deployment --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/matlab/agent-skills-playground.git skills-src && mkdir -p .agents/skills && cp -r skills-src/demos/embedded-ai-deployment/skills/embedded-ai-deployment .agents/skills/embedded-ai-deployment && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "embedded-ai-deployment" agent skill from https://github.com/matlab/agent-skills-playground/tree/main/demos/embedded-ai-deployment/skills/embedded-ai-deployment into .agents/skills/embedded-ai-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "embedded-ai-deployment", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add matlab/agent-skills-playground --skill embedded-ai-deployment -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install matlab/agent-skills-playground embedded-ai-deployment --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/matlab/agent-skills-playground.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/demos/embedded-ai-deployment/skills/embedded-ai-deployment .cursor/skills/embedded-ai-deployment && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "embedded-ai-deployment" agent skill from https://github.com/matlab/agent-skills-playground/tree/main/demos/embedded-ai-deployment/skills/embedded-ai-deployment into .cursor/skills/embedded-ai-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "embedded-ai-deployment", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/matlab/agent-skills-playground.git --path demos/embedded-ai-deployment/skills/embedded-ai-deployment--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add matlab/agent-skills-playground --skill embedded-ai-deployment -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install matlab/agent-skills-playground embedded-ai-deployment --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/matlab/agent-skills-playground.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/demos/embedded-ai-deployment/skills/embedded-ai-deployment .gemini/skills/embedded-ai-deployment && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "embedded-ai-deployment" agent skill from https://github.com/matlab/agent-skills-playground/tree/main/demos/embedded-ai-deployment/skills/embedded-ai-deployment into .gemini/skills/embedded-ai-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "embedded-ai-deployment", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install matlab/agent-skills-playground embedded-ai-deploymentInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add matlab/agent-skills-playground --skill embedded-ai-deployment -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/matlab/agent-skills-playground.git skills-src && mkdir -p .github/skills && cp -r skills-src/demos/embedded-ai-deployment/skills/embedded-ai-deployment .github/skills/embedded-ai-deployment && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "embedded-ai-deployment" agent skill from https://github.com/matlab/agent-skills-playground/tree/main/demos/embedded-ai-deployment/skills/embedded-ai-deployment into .github/skills/embedded-ai-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "embedded-ai-deployment", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add matlab/agent-skills-playground --skill embedded-ai-deployment -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install matlab/agent-skills-playground embedded-ai-deployment --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/matlab/agent-skills-playground.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/demos/embedded-ai-deployment/skills/embedded-ai-deployment .opencode/skills/embedded-ai-deployment && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "embedded-ai-deployment" agent skill from https://github.com/matlab/agent-skills-playground/tree/main/demos/embedded-ai-deployment/skills/embedded-ai-deployment into .opencode/skills/embedded-ai-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "embedded-ai-deployment", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
embedded-ai-deployment- GitHub stars
- 181
- Used in
- 1 other repo
- Token cost
- ~3.4k tokens
- SKILL.md length
- 1,449 words
- Files
- 24 (incl. references)
- Skills in repo
- 29
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Deploy AI models to embedded hardware using MathWorks tools (MATLAB, Simulink, Embedded Coder).
- Works in 2 steps: Environment Discovery (silent): Load… → Project Discovery (interactive): Load…
- : user wants to deploy AI to embedded targets
- SKILL.md covers Workflow Pattern Selection, Common Start: Prerequisites, Banned Legacy Functions and Global Rules
- Reaches mathworks.com
What it does
Embedded AI Deployment is an agent skill from matlab/agent-skills-playground. Deploy AI models to embedded hardware using MathWorks tools (MATLAB, Simulink, Embedded Coder). Covers two workflow patterns: (1) MathWorks-native or 3P-imported models rebuilt as dlnetwork for lean hardware (Cortex-M, DSP), (2) direct C/C++ code generation from PyTorch and LiteRT models for high-performance hardware (Cortex-A, x86, GPU). Trigger when: user wants to deploy AI to embedded targets; generate C/CUDA from neural networks; compress AI models for MCU/DSP; integrate AI in Simulink for system-level…
Its SKILL.md is about 3.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 27 other files, including reference files (for example `agents/openai.yaml`, `references/pattern1/codegen-embedded.md` and `references/pattern1/compression-decision.md`).
It sits in AI & LLM Engineering, covering Deep learning and Deployment. It works with PyTorch, TensorFlow, C++ and CUDA. The repository describes itself as: A sandbox for prototyping and demonstrating Agent Skills for MATLAB and Simulink work.
When your agent uses it
- : user wants to deploy AI to embedded targets
- Generate C/CUDA from neural networks
- Compress AI models for MCU/DSP
- Integrate AI in Simulink for system-level simulation
Example prompts
- “/embedded-ai-deployment”
Requirements
- Python 3
Workflow steps
2 steps, taken from the first numbered list in SKILL.md.
- Environment Discovery (silent): Load references/shared/environment-setup.md
- Project Discovery (interactive): Load references/shared/project-discovery.md
What it can do on your machine
Read from SKILL.md and the folder at commit 7b14a77. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
mathworks.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Embedded AI Deployment loads about 3.4k tokens when it runs, and up to ~63k if it reads all its reference files. Until then it costs about 197 tokens; SKILL.md has 1,449 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 1,449 words (~3,369 tokens).
“Deploy AI models to embedded hardware using MATLAB® and Simulink®. This skill is written specifically for MATLAB R2026a and uses APIs, functions, and workflows introduced in that release. It covers the complete lifecycle: model creation or import, verification, compression, system-level…”
- name
- embedded-ai-deployment
- license
- https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
- metadata.author
- MathWorks
- metadata.version
- 1.0
Files
SKILL.md and 23 other files (references) in demos/embedded-ai-deployment/skills/embedded-ai-deployment of matlab/agent-skills-playground.
- SKILL.md
- agents/openai.yaml
- references/pattern1/codegen-embedded.md
- references/pattern1/compression-decision.md
- references/pattern1/compression.md
- references/pattern1/custom-layers-codegen.md
- references/pattern1/data-preparation.md
- references/pattern1/import-weight-extraction.md
- references/pattern1/native-rebuild-patterns.md
- references/pattern1/placeholder-blocks.md
- references/pattern1/simulink-integration.md
- references/pattern1/training-native.md
- references/pattern1/troubleshooting.md
- references/pattern1/workflow.md
- references/pattern2/architecture-patterns.md
- references/pattern2/coder-configuration.md
- references/pattern2/pytorch-export.md
- … and 7 more
Open the folder on GitHubat commit 7b14a77
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in matlab/agent-skills-playground, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Embedded AI Deployment next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Embedded AI Deployment this skillmatlab/agent-skills-playground | 181 | 1 repos | ~3.4k | Automated safety check: Pass | Custom licence | |
| Matlab Deploy Embedded AImajiayu000/claude-skill-registry | 666 | 1 repos | ~4.6k | Automated safety check: Pass | MIT | |
| Matlab Deploy AI Modelmatlab/matlab-agentic-toolkit | 1.1k | — | ~2.8k | Automated safety check: Pass | Custom licence | |
| Ako4allTongmingLAIC/AKO4ALL | 369 | — | ~4k | Automated safety check: Pass | MIT | |
| Paddle Op DevPaddlePaddle/Paddle | 24k | — | ~1.3k | Automated safety check: Pass | Apache-2.0 | |
| At Dispatch V2intel/torch-xpu-ops | 115 | 3 repos | ~2.2k | Automated safety check: Pass | Apache-2.0 |
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Questions about Embedded AI Deployment
What does Embedded AI Deployment do?
Deploy AI models to embedded hardware using MathWorks tools (MATLAB, Simulink, Embedded Coder). Embedded AI Deployment is an agent skill from matlab/agent-skills-playground. Deploy AI models to embedded hardware using MathWorks tools (MATLAB, Simulink, Embedded Coder).
When should I use Embedded AI Deployment?
Embedded AI Deployment fits situations like: : user wants to deploy AI to embedded targets; generate C/CUDA from neural networks; compress AI models for MCU/DSP; integrate AI in Simulink for system-level simulation.
How do I install Embedded AI Deployment in Claude Code?
Run `npx skills add matlab/agent-skills-playground --skill embedded-ai-deployment -a claude-code`. Or copy the skill folder (demos/embedded-ai-deployment/skills/embedded-ai-deployment in matlab/agent-skills-playground) into .claude/skills/embedded-ai-deployment in your project. Claude Code loads it when a task matches its description.
How do I install Embedded AI Deployment in Codex?
Run `npx skills add matlab/agent-skills-playground --skill embedded-ai-deployment -a codex`. Or copy the skill folder (demos/embedded-ai-deployment/skills/embedded-ai-deployment in matlab/agent-skills-playground) into .agents/skills/embedded-ai-deployment in your project. Codex loads it when a task matches its description.
Can I use Embedded AI Deployment in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add matlab/agent-skills-playground --skill embedded-ai-deployment -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/embedded-ai-deployment, .gemini/skills/embedded-ai-deployment, .github/skills/embedded-ai-deployment and .opencode/skills/embedded-ai-deployment in your project.
What does Embedded AI Deployment need to run?
SKILL.md names no scripts, command-line tools or credentials: Embedded AI Deployment is instructions for the agent only. Our summary lists: Python 3.
Does Embedded AI Deployment access the network?
SKILL.md names 1 domain. In commands or code: mathworks.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Is Embedded AI Deployment safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Embedded AI Deployment use?
Embedded AI Deployment has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
How many tokens does Embedded AI Deployment use?
About 3.4k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 59k tokens, read only when the agent opens those files.
What are the alternatives to Embedded AI Deployment?
Skills that share tags, products or a category with Embedded AI Deployment: Matlab Deploy Embedded AI (majiayu000/claude-skill-registry, 666 stars), Matlab Deploy AI Model (matlab/matlab-agentic-toolkit, 1.1k stars), Ako4all (TongmingLAIC/AKO4ALL, 369 stars) and Paddle Op Dev (PaddlePaddle/Paddle, 24k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Embedded AI Deployment?
matlab (a GitHub organization) maintains it in matlab/agent-skills-playground, which has 181 GitHub stars. The repository holds 29 skills in this directory. The repository was last updated on September 10, 2026.
Source: matlab/agent-skills-playground on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.