Matlab Performance Optimizer
CheckedAutomatically identifies and suggests MATLAB code optimizations to improve script execution speed and efficiency.
Install on your platform
Showing Claude Code. One command installs this skill into any of the agents below.
- 1
Run this in your project
terminal$ npx skills add matlab/agent-skills-playground --skill matlab-performance-optimizer -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto install it for your user instead of this project.
What we know about this skill
Publisher
matlab
Taken from the source listing. We haven't verified who controls this account.
Install target
Live repository
Not pinned. Installing fetches whatever the repository holds at the time you run the command.
Automated safety checks
This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.
Declares what it does: passed
SKILL.md parses and declares a name and a description.
SKILL.md exists, its frontmatter parses, and it declares a name and a description.
No undeclared network calls: passed
Makes no network calls.
Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.
No obfuscated payloads: passed
No encoded or obfuscated payloads.
No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.
No credential access: passed
Reads no keys, tokens, keychains or credential files.
Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.
No pipe-to-shell installers: passed
No pipe-to-shell or download-and-run installers.
No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.
Pinned to a commit: passed
Scanned matlab/skills at 7b14a7756b.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- 7b14a7756b
- Scanned
- 1 file, 548 lines
About this skill
What it does
The matlab-performance-optimizer skill allows AI agents to analyze and optimize MATLAB code for improved performance. It identifies bottlenecks, suggests algorithmic improvements, and provides recommendations for efficient memory usage within MATLAB scripts and functions. This results in faster execution times and reduced resource consumption for computationally intensive tasks.
When to use it
- Slow Simulations: Optimize lengthy simulations or models that take an unacceptably long time to run.
- Large Datasets: Improve the processing speed of code dealing with substantial datasets within MATLAB.
- Resource Constraints: Reduce memory usage and CPU load when running MATLAB on systems with limited resources.
- Code Refactoring: Get assistance in identifying areas for improvement during a broader code refactoring effort.
Key capabilities
- Performance bottleneck identification
- Algorithmic optimization suggestions
- Memory usage analysis
- MATLAB code profiling
Example prompts
- "Analyze this MATLAB script and suggest ways to improve its performance." (followed by the script)
- "What are the bottlenecks in my
my_simulation.mfile?" - "Optimize this function for faster execution: [function definition]"
Tips & gotchas
The skill requires access to the MATLAB code being analyzed. Ensure the AI agent has appropriate permissions and context to effectively interpret and provide optimization suggestions.