Claude-skill-registry go-performance

Go performance optimization - profiling, benchmarks, memory management

install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/go-performance" ~/.claude/skills/majiayu000-claude-skill-registry-go-performance && rm -rf "$T"
manifest: skills/data/go-performance/SKILL.md
source content

Go Performance Skill

Optimize Go application performance with profiling and best practices.

Overview

Comprehensive performance optimization including CPU/memory profiling, benchmarking, and common optimization patterns.

Parameters

ParameterTypeRequiredDefaultDescription
profile_typestringyes-Type: "cpu", "memory", "goroutine", "block"
durationstringno"30s"Profile duration

Core Topics

pprof Setup

import (
    "net/http"
    _ "net/http/pprof"
)

func main() {
    // Start pprof server
    go func() {
        http.ListenAndServe("localhost:6060", nil)
    }()

    // Your application
    runApp()
}

CPU Profiling

# Collect 30s CPU profile
go tool pprof http://localhost:6060/debug/pprof/profile?seconds=30

# Interactive commands
(pprof) top 10          # Top 10 CPU consumers
(pprof) list funcName   # Source view
(pprof) web             # Open in browser
(pprof) svg > cpu.svg   # Export SVG

Memory Profiling

# Heap profile
go tool pprof http://localhost:6060/debug/pprof/heap

# Allocs since start
go tool pprof http://localhost:6060/debug/pprof/allocs

(pprof) top --cum       # By cumulative allocations
(pprof) list funcName   # Where allocations happen

Benchmarking

func BenchmarkProcess(b *testing.B) {
    data := setupData()

    b.ResetTimer()
    b.ReportAllocs()

    for i := 0; i < b.N; i++ {
        Process(data)
    }
}

func BenchmarkProcess_Parallel(b *testing.B) {
    data := setupData()

    b.RunParallel(func(pb *testing.PB) {
        for pb.Next() {
            Process(data)
        }
    })
}
# Run benchmarks
go test -bench=. -benchmem ./...

# Compare benchmarks
go test -bench=. -count=5 > old.txt
# make changes
go test -bench=. -count=5 > new.txt
benchstat old.txt new.txt

Memory Optimization

// Preallocate slices
func ProcessItems(items []Item) []Result {
    results := make([]Result, 0, len(items)) // Preallocate
    for _, item := range items {
        results = append(results, process(item))
    }
    return results
}

// Use sync.Pool for frequent allocations
var bufferPool = sync.Pool{
    New: func() interface{} {
        return new(bytes.Buffer)
    },
}

func GetBuffer() *bytes.Buffer {
    buf := bufferPool.Get().(*bytes.Buffer)
    buf.Reset()
    return buf
}

func PutBuffer(buf *bytes.Buffer) {
    bufferPool.Put(buf)
}

Escape Analysis

# Check what escapes to heap
go build -gcflags="-m -m" ./...

# Common escapes
# - Returning pointers to local variables
# - Storing in interface{}
# - Closures capturing variables

Optimization Patterns

// String building - use strings.Builder
var b strings.Builder
for _, s := range parts {
    b.WriteString(s)
}
result := b.String()

// Avoid interface{} in hot paths
// Use generics or concrete types

// Reduce allocations in loops
buffer := make([]byte, 1024)
for {
    n, err := reader.Read(buffer)
    // reuse buffer
}

Profiling Commands

# Goroutine profile (leak detection)
go tool pprof http://localhost:6060/debug/pprof/goroutine

# Block profile (contention)
go tool pprof http://localhost:6060/debug/pprof/block

# Mutex profile
go tool pprof http://localhost:6060/debug/pprof/mutex

# Trace (detailed execution)
curl -o trace.out http://localhost:6060/debug/pprof/trace?seconds=5
go tool trace trace.out

Troubleshooting

Failure Modes

SymptomCauseFix
High CPUHot loop, GCProfile, reduce allocs
High memoryLeak, no poolingHeap profile, sync.Pool
Slow startLarge initLazy initialization
GC pausesMany allocationsReduce allocations

Usage

Skill("go-performance")