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Maui Performance

Checked
davidortinau·vlatest·other·MIT

Analyzes code execution profiles to identify performance bottlenecks and suggest optimization strategies using Maui metrics.

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add davidortinau/maui-skills --skill maui-performance -a claude-code
  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

davidortinau

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.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

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 davidortinau/maui-skills at 79bb4bfd8f.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Scanned
1 file, 122 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The maui-performance skill optimizes AI agent performance. It likely focuses on improving speed, efficiency, and resource utilization within an AI agent's workflow. This can involve techniques like caching, code profiling, and algorithmic optimization to ensure faster response times and reduced computational load.

When to use it

  • Slow Response Times: When your AI agent is taking too long to respond to user requests or complete tasks.
  • High Resource Consumption: If the AI agent is consuming excessive CPU, memory, or other resources.
  • Complex Workflows: For agents handling intricate processes that require significant computational power.
  • Real-time Applications: When low latency and quick processing are critical for a real-time application.

Key capabilities

  • Performance optimization
  • Resource utilization improvement
  • Speed enhancement
  • Efficiency gains

Example prompts

  • "Optimize the performance of my agent's summarization module."
  • "Can you profile the resource usage of this AI agent workflow?"
  • "Improve the speed of the data processing pipeline for my agent."

Tips & gotchas

The skill’s effectiveness depends on the underlying code and architecture of the AI agent. It may require some level of technical understanding to interpret profiling results or implement suggested optimizations.