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Samuelca6399
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performance-engineering

Diagnose application performance by measuring CPU, memory, latency percentiles, and throughput.

Updated Aug 27, 2026
Search Tags:#performance#benchmarking#memory leak#profiling#latency#flame graph#heap snapshot
One-click install
npx skills add https://github.com/Samuelca6399/AbsolutelySkilled --skill performance-engineering-samuelca6399
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: performance-engineering
Source: https://github.com/Samuelca6399/AbsolutelySkilled/tree/main/skills/performance-engineering
Command: npx skills add https://github.com/Samuelca6399/AbsolutelySkilled --skill performance-engineering-samuelca6399

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you diagnose and improve slow, inefficient, or memory-leaking applications by turning performance work into a measurable workflow rather than guesswork.

Core Features & Use Cases

  • CPU Profiling & Flame Graphs: Identify hot functions, long tasks, and event-loop bottlenecks using tools like 0x, clinic.js, and built-in profilers.
  • Memory Leak Investigation: Capture and compare heap snapshots to find objects that keep accumulating across a workload window.
  • Benchmarking & Optimization Validation: Run fair microbenchmarks and confirm improvements with percentiles (P50/P95/P99), budgets, and realistic load testing.

Quick Start

Ask for a diagnosis and next commands by saying: "Use performance-engineering to investigate why our P99 latency regressed after the last deploy and outline the exact profiling and benchmarking steps."

Frequently Asked Questions about performance-engineering

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

FAQPage Schema
How do I find a memory leak using heap snapshots?▼

Memory leak investigation involves capturing and comparing heap snapshots across a workload window to isolate accumulating objects. This measure-first approach validates the leak before applying fixes.

How do I diagnose high P99 latency after a deployment?▼

Diagnose P99 latency regression by profiling CPU hot functions, analyzing event-loop blocking, and running fair microbenchmarks. Use percentile budgets and realistic load testing to validate improvements.

What is the best way to identify CPU bottlenecks with flame graphs?▼

CPU profiling with flame graphs identifies hot functions and long tasks using toolchains like 0x and clinic.js. This visualizes call stacks to locate event-loop bottlenecks and optimize execution paths.

How do I set up fair microbenchmarks to validate performance improvements?▼

Set up fair microbenchmarks by measuring throughput and latency percentiles (P50, P95, P99) across production-like workloads. This validates optimizations with empirical data rather than assumptions.

When do I need event-loop blocking analysis for my application?▼

Event-loop blocking analysis is needed when profiling reveals long tasks or hot functions degrading throughput. It isolates synchronous operations stalling the loop, guiding targeted CPU optimizations.

Can I reduce frontend bundle size and optimize database queries with this profiling approach?▼

Frontend bundle reduction and database query optimization fit this measure-first profiling approach. It diagnoses bottlenecks by applying profiling toolchains and decision rules that focus on validated improvements.

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