performance-optimization

Measure, profile, and fix performance bottlenecks in web apps, APIs, and database queries.

2|1|Updated Apr 13, 2026

Search Tags:#frontend #backend #lighthouse #optimize #profile #core-web-vitals #measure

Ready to run

npx skills add https://github.com/dreamingechoes/dx-toolkit --skill performance-optimization-dreamingechoes

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: performance-optimization
Source: https://github.com/dreamingechoes/dx-toolkit/tree/main/templates/skills/performance-optimization
Command: npx skills add https://github.com/dreamingechoes/dx-toolkit --skill performance-optimization-dreamingechoes

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps teams measure, identify, and fix performance bottlenecks by following a disciplined measure-first approach. It emphasizes validating improvements with concrete data rather than guesswork, to deliver measurable performance gains.

Core Features & Use Cases

Baseline measurement: establish performance metrics (response time, TTFB, LCP, bundle size) before changes.
Bottleneck identification: pinpoint bottlenecks using profiling, tracing, and performance budgets across frontend and backend.
Safe fixes and verification: apply minimal changes, re-measure, and compare results to prove improvements.
Use cases include improving page load times, API latency, and database query performance in production or staging environments.

Quick Start

Run a baseline performance audit on your app and document metrics, then profile the bottleneck and implement a fix.

Frequently Asked Questions about performance-optimization

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

FAQPage Schema

How do I identify frontend performance bottlenecks using core web vitals?▼

Identify frontend performance bottlenecks by measuring baseline metrics like LCP and TTI, then using profiling and tracing to pinpoint issues before applying minimal fixes and verifying improvements with repeatable benchmarks.

What's the best way to measure API response time and database query latency?▼

Measure API response time and database query latency by establishing a performance baseline in staging or production, profiling the backend bottlenecks, applying targeted fixes, and re-measuring to prove the latency improvements.

How does a measure-first approach improve web app performance?▼

A measure-first approach improves web app performance by validating fixes with concrete data rather than guesswork, ensuring you document baseline metrics like bundle size and TTFB before applying changes to prove measurable gains.

Can I use this measure-first optimization workflow for both frontend and backend systems?▼

Yes, you can use this measure-first optimization workflow for both frontend and backend systems, applying profiling and performance budgets across web apps, APIs, and database queries to validate improvements in production or staging environments.

How do I verify performance improvements after optimizing bundle size and load times?▼

Verify performance improvements after optimizing bundle size and load times by re-measuring the baseline metrics using repeatable tooling and benchmarks, comparing the new results against the initial data to prove the gains.

Why should I establish a performance baseline before fixing bottlenecks?▼

You should establish a performance baseline before fixing bottlenecks to document current metrics like response time, TTFB, LCP, and bundle size, providing a concrete reference point to validate that your minimal fixes deliver measurable improvements.