用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/pluginagentmarketplace/custom-plugin-go --skill go-performance命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
基于 SOC 职业分类
| name | go-performance |
| description | Go performance optimization - profiling, benchmarks, memory management |
| sasmp_version | 1.3.0 |
| bonded_agent | 02-go-concurrency |
| bond_type | SECONDARY_BOND |
Optimize Go application performance with profiling and best practices.
Comprehensive performance optimization including CPU/memory profiling, benchmarking, and common optimization patterns.
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| profile_type | string | yes | - | Type: "cpu", "memory", "goroutine", "block" |
| duration | string | no | "30s" | Profile duration |
import (
"net/http"
_ "net/http/pprof"
)
func main() {
// Start pprof server
go func() {
http.ListenAndServe("localhost:6060", nil)
}()
// Your application
runApp()
}
# 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
# 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
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
// 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)
}
# Check what escapes to heap
go build -gcflags="-m -m" ./...
# Common escapes
# - Returning pointers to local variables
# - Storing in interface{}
# - Closures capturing variables
// 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
}
# 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
| Symptom | Cause | Fix |
|---|---|---|
| High CPU | Hot loop, GC | Profile, reduce allocs |
| High memory | Leak, no pooling | Heap profile, sync.Pool |
| Slow start | Large init | Lazy initialization |
| GC pauses | Many allocations | Reduce allocations |
Skill("go-performance")