lens-performance

Review code for performance issues across Android, iOS, Web, and Backend platforms.

Updated Aug 26, 2025
One-click install
npx skills add https://github.com/ThonkTank/Salt-Marcher --skill lens-performance
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: lens-performance
Source: https://github.com/ThonkTank/Salt-Marcher/tree/main/tools/quality/skills/lens-performance
Command: npx skills add https://github.com/ThonkTank/Salt-Marcher --skill lens-performance

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill identifies and addresses performance bottlenecks in code, ensuring smooth operation across platforms and devices.

Core Features & Use Cases

  • Performance Review: Analyze code for memory leaks, query efficiency, main-thread blocking, and more.
  • Platform-Specific Analysis: Tailored guidance for Android, iOS, Web, Backend, and cross-platform scenarios.
  • Use Case: Before deploying a new feature, use this Skill to ensure it won't introduce lag or memory issues on low-end devices.

Quick Start

Run the lens-performance skill on your codebase to identify performance issues.

Frequently Asked Questions about lens-performance

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze my codebase for memory leaks and GC pressure?

Memory leak analysis reviews your codebase for hot-path allocations and GC pressure. It identifies performance bottlenecks across platforms to ensure smooth operation on low-end devices before deployment.

What causes main-thread blocking and how can I identify it in my code?

Main-thread blocking is identified by reviewing your codebase for synchronous operations causing lag. Performance analysis detects these issues and provides platform-specific guidance to resolve rendering and startup time concerns.

Can I use performance analysis for both Android and iOS platforms?

Yes, performance analysis supports Android, iOS, Web, and Backend platforms. It provides tailored guidance for cross-platform scenarios to address memory issues, bundle size, and rendering concerns specific to each environment.

What's the best way to optimize algorithmic complexity before deploying a new feature?

The best way to optimize algorithmic complexity is running a deep performance review on your codebase. This analyzes query efficiency and main-thread blocking, providing expert insights to ensure new features won't introduce lag.

Does this performance review work for backend query efficiency and startup time?

Yes, performance review works for backend query efficiency and startup time. It analyzes your codebase across platforms including Backend, identifying hot-path allocations and algorithmic complexity issues to ensure smooth operation.

Why does my code have high GC pressure on low-end devices?

High GC pressure on low-end devices is caused by hot-path allocations in your code. Performance analysis reviews your codebase to identify these memory issues and bundle size concerns, providing tailored guidance to resolve them.