go-performance

Profile Go services with pprof and benchstat to identify performance bottlenecks.

1|Updated Feb 19, 2026

Search Tags:#performance #benchmarking #go #profiling #code-review #pprof #gc-tuning

Ready to run

npx skills add https://github.com/juburr/mad-skills --skill go-performance-juburr

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: go-performance
Source: https://github.com/juburr/mad-skills/tree/main/go-performance
Command: npx skills add https://github.com/juburr/mad-skills --skill go-performance-juburr

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Go performance skills help engineering teams systematically optimize Go services for throughput and latency by teaching measurement-first practices, benchmarking, and profiling to locate bottlenecks.

Core Features & Use Cases

Measurement-first workflow that starts with baselines, bottleneck classification, profiling, and iterative improvements.
Benchmarking and profiling guidance for CPU time, allocations/GC, memory footprint, contention, and I/O overhead, with practical examples using pprof, benchstat, and runtime metrics.
Production-oriented patterns for scalable Go services, including GC tuning, trace-based diagnosis, and production profiling recommendations.

Quick Start

Execute a measurement-first review on a Go service to identify bottlenecks and apply targeted performance fixes.

Frequently Asked Questions about go-performance

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

FAQPage Schema

How do I find bottlenecks in a Go service using profiling?▼

Find bottlenecks in your Go service by applying measurement-based profiling to CPU, memory/GC, contention, and I/O across server workloads to identify performance limitations and propose targeted improvements.

What is a measurement-first workflow for Go performance optimization?▼

A measurement-first workflow for Go performance optimization starts with baselines, bottleneck classification, profiling, and iterative improvements to systematically locate and resolve throughput and latency bottlenecks.

How do I write reproducible benchmarks for Go microservices?▼

Write reproducible benchmarks for Go microservices using practical examples with pprof, benchstat, and runtime metrics to measure CPU time, allocations/GC, memory footprint, and I/O overhead.

Can I use pprof for GC tuning and trace-based diagnosis in production Go applications?▼

Yes, you can use pprof for GC tuning and trace-based diagnosis in production Go applications by applying production-oriented patterns and profiling recommendations to sustain performance gains.

What's the best way to reduce memory allocations and GC overhead in Go?▼

Reduce memory allocations and GC overhead in Go by following actionable code-review guidance and profiling allocations/GC and memory footprint to apply targeted performance fixes.

When should I profile contention and I/O overhead in Go server workloads?▼

Profile contention and I/O overhead in Go server workloads when identifying bottlenecks across microservices, applying measurement-based profiling to propose targeted performance improvements.