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Performance Profiling

Checked
vudovn·vlatest·testing·MIT

Analyzes application performance bottlenecks and resource usage to optimize efficiency through detailed profiling reports.

Repository

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 vudovn/ag-kit --skill performance-profiling -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

vudovn

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 vudovn/ag-kit at 549ba3dc2e.

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

Commit
549ba3dc2e
Manifest
.agents/skills/performance-profiling/SKILL.md
Scanned
3 files, 374 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

This skill enables AI agents to analyze application performance bottlenecks and resource usage, ultimately helping optimize efficiency through detailed profiling reports. It provides tools and workflows for measuring key metrics like Core Web Vitals (LCP, INP, CLS), bundle size, runtime behavior, and memory consumption. The goal is to identify areas for improvement and validate the impact of optimizations.

When to use it

This skill is useful in several scenarios:

  • Development: Identifying performance issues early on during local development.
  • CI/CD Pipelines: Automating performance audits as part of continuous integration and delivery processes.
  • Production Monitoring: Analyzing real user monitoring (RUM) data to understand how users experience the application.
  • Troubleshooting Slow Interactions: Investigating slow page loads, sluggish interactions, or janky scrolling.
  • Memory Leak Detection: Identifying potential memory leaks and retained references impacting application stability.

Key capabilities

  • Lighthouse Audits: Executes Lighthouse audits to measure Core Web Vitals.
  • Bundle Analysis: Identifies issues within JavaScript bundles like large dependencies, duplicate code, and unused exports.
  • Runtime Profiling: Analyzes performance using browser DevTools Performance tab (long tasks, layout/paint bottlenecks) and Memory tab (heap growth, detached DOM).
  • Profiling Workflow: Guides a 4-step process: Baseline, Identify, Fix, Validate.
  • Script Execution: Provides scripts like lighthouse_audit.py for automated profiling.

Example prompts

  • "Run a Lighthouse audit on example.com."
  • "Analyze the JavaScript bundle size and identify potential optimizations."
  • "Profile the runtime performance of this application and look for long tasks."

Tips & gotchas

  • Prioritize: Focus on fixing the biggest bottlenecks first, rather than micro-optimizing.
  • Baseline First: Always establish a baseline measurement before making changes to accurately assess improvements.
  • RUM Data is Key: Use real user monitoring (RUM) data for production performance insights.