go-performance

Optimize Go performance by reducing allocations, memory usage, and I/O overhead.

2|Updated Jan 3, 2026
One-click install
npx skills add https://github.com/jovermier/cc-stack-marketplace --skill go-performance
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: go-performance
Source: https://github.com/jovermier/cc-stack-marketplace/tree/main/plugins/cc-go/skills/go-performance
Command: npx skills add https://github.com/jovermier/cc-stack-marketplace --skill go-performance

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill guides Go developers to reduce allocations, optimize string processing, and streamline I/O to achieve faster, more memory-efficient applications.

Core Features & Use Cases

  • Memory allocation reduction: patterns and idioms that minimize allocations and GC pressure.
  • Efficient string building: using strings.Builder to avoid O(n^2) string concatenation.
  • Pooling and re-use: applying sync.Pool to reuse objects and reduce churn.
  • Buffered I/O: employing bufio and buffered writers/readers to lower syscalls.
  • Benchmarking focus: measuring improvements to validate optimizations with repeatable tests.

Quick Start

Apply these practices to an existing Go function by replacing repeated string concatenations with a strings.Builder, wrap frequently allocated objects with a sync.Pool, and switch to buffered I/O where appropriate.

Frequently Asked Questions about go-performance

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

FAQPage Schema
How do I reduce memory allocations in Go to speed up my application?

Reduce memory allocations in Go by applying patterns like strings.Builder for concatenation, sync.Pool for object reuse, and buffered I/O to minimize syscalls and GC pressure.

Why does string concatenation cause high memory usage in Go and how do I fix it?

String concatenation in Go causes high memory usage due to O(n^2) allocation overhead; fix it by using strings.Builder to efficiently append text without creating intermediate string copies.

What is the best way to measure Go performance improvements after optimizing memory usage?

The best way to measure Go performance improvements is through benchmarking with repeatable tests, validating that reductions in allocations and memory churn actually translate to faster execution.

Can I use sync.Pool to reuse objects and reduce garbage collection overhead in Go?

Yes, you can use sync.Pool in Go to reuse frequently allocated objects, effectively reducing churn and lowering garbage collection overhead across typical services and codebases.

Does buffered I/O help lower syscall overhead in Go applications?

Buffered I/O helps lower syscall overhead in Go applications by employing bufio buffered readers and writers, which reduces the frequency of expensive system calls during read and write operations.

When should I not use sync.Pool for memory optimization in Go?

You should not use sync.Pool for memory optimization in Go when objects vary significantly in size or when benchmarking fails to verify measurable gains, as pooling overhead might outweigh allocation savings.