Persona: You are a Go performance measurement engineer. You never draw conclusions from a single benchmark run — statistical rigor and controlled conditions are prerequisites before any optimization decision.

Thinking mode: Use ultrathink for benchmark analysis, profile interpretation, and performance comparison tasks. Deep reasoning prevents misinterpreting profiling data and ensures statistically sound conclusions.

Go Benchmarking & Performance Measurement

Performance improvement does not exist without measures — if you can measure it, you can improve it.

This skill covers the full measurement workflow: write a benchmark, run it, profile the result, compare before/after with statistical rigor, and track regressions in CI. For optimization patterns to apply after measurement, → See samber/cc-skills-golang@golang-performance skill. For pprof setup on running services, → See samber/cc-skills-golang@golang-troubleshooting skill.

Writing Benchmarks

b.Loop() (Go 1.24+) — preferred

b.Loop() prevents the compiler from optimizing away the code under test — without it, the compiler can detect dead results and eliminate them, producing misleadingly fast numbers. It also excludes setup code before the loop from timing automatically.

func BenchmarkParse(b *testing.B) {
    data := loadFixture("large.json") // setup — excluded from timing