golang-benchmark

Analyze Go performance with benchmarking, profiling, and comparison workflows.

Updated Aug 27, 2026

Search Tags:#benchmarking #go #profiling #tracing #pprof #benchstat #benchdiff

Ready to run

npx skills add https://github.com/nrmnqdds/gomaluum --skill golang-benchmark-nrmnqdds

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: golang-benchmark
Source: https://github.com/nrmnqdds/gomaluum/tree/main/.agents/skills/golang-benchmark
Command: npx skills add https://github.com/nrmnqdds/gomaluum --skill golang-benchmark-nrmnqdds

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Go performance measurement is essential for Go projects; this skill provides a complete workflow for benchmarking, profiling, and comparing results to identify bottlenecks and regressions.

Core Features & Use Cases

Deterministic benchmarking patterns using b.Loop to ensure valid timing.
Performance analysis workflow leveraging pprof, benchstat, benchdiff, and traces for deep insights.
Use cases include optimizing hot paths, CI performance gates, and long-term trend tracking.

Quick Start

Run a baseline Go benchmark and compare it to updates using benchstat or benchdiff.

Frequently Asked Questions about golang-benchmark

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

FAQPage Schema

How do I use benchstat and benchdiff to detect Go benchmark regressions?▼

Use benchstat and benchdiff to compare baseline and updated Go benchmark results, applying statistical analysis to detect performance regressions across code changes. This workflow ensures rigorous regression detection by highlighting statistically significant timing differences between benchmark runs.

How does b.Loop improve deterministic benchmarking in Go?▼

b.Loop improves deterministic benchmarking in Go by ensuring valid timing and consistent iteration execution. This approach eliminates previous benchmarking overhead, providing reliable performance measurements for accurate profiling and regression detection across your codebase.

What is the best way to analyze Go hot paths using pprof and traces?▼

Analyze Go hot paths by running benchmarks and leveraging pprof and trace tools to capture deep performance insights. This workflow identifies bottlenecks by visualizing CPU usage and execution traces, allowing you to pinpoint and optimize critical code paths effectively.

Can I set up CI performance gates using Go benchmarks?▼

Yes, you can establish CI performance gates by integrating Go benchmarks with benchstat or benchdiff to automatically block code changes that introduce performance regressions. This ensures long-term trend tracking and maintains optimal hot path execution efficiency.

When do I need to use benchstat for Go profiling instead of just running benchmarks?▼

You need benchstat when comparing benchmark results to determine if performance changes are statistically significant rather than just timing noise. It provides the statistical validation required for reliable regression detection and long-term performance trend analysis.