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go-performance围棋表演

Agent Skill

go-performance 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

11,481

周安装

469

GitHub Stars

81

下载量

3,677
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:go-performance(围棋表演)
来源仓库:https://github.com/cxuu/golang-skills
仓库路径:skills/go-performance
安装命令:
npx skills add https://github.com/cxuu/golang-skills --skill go-performance
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/cxuu/golang-skills --skill go-performance

简介

Go 性能模式聚焦热路径优化与内存分配控制。

  • 适用于高频调用函数与大数据处理场景提速。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。
  • strconv 优于 fmt 进行基本类型转字符串。
  • 仅优化已验证瓶颈,避免过早优化引入复杂性。
  • go-performance 属于待分类类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Go Performance Patterns

Available Scripts

  • scripts/bench-compare.sh — Runs Go benchmarks N times with optional baseline comparison via benchstat. Supports saving results for future comparison. Run bash scripts/bench-compare.sh --help for options.

Performance-specific guidelines apply only to the hot path. Don't prematurely optimize—focus these patterns where they matter most.


Prefer strconv over fmt

When converting primitives to/from strings, strconv is faster than fmt:

s := strconv.Itoa(rand.Int()) // ~2x faster than fmt.Sprint()
ApproachSpeedAllocations
fmt.Sprint143 ns/op2 allocs/op
strconv.Itoa64.2 ns/op1 allocs/op
Read references/STRING-OPTIMIZATION.md when choosing between strconv and fmt for type conversions, or for the full conversion table.

Avoid Repeated String-to-Byte Conversions

Convert a fixed string to []byte once outside the loop:

data := []byte("Hello world")
for i := 0; i < b.N; i++ {
    w.Write(data) // ~7x faster than []byte("...") each iteration
}
Read references/STRING-OPTIMIZATION.md when optimizing repeated byte conversions in hot loops.

Prefer Specifying Container Capacity

Specify container capacity where possible to allocate memory up front. This minimizes subsequent allocations from copying and resizing as elements are added.

Map Capacity Hints

Provide capacity hints when initializing maps with make():

m := make(map[string]os.DirEntry, len(files))

Note: Unlike slices, map capacity hints do not guarantee complete preemptive allocation—they approximate the number of hashmap buckets required.

Slice Capacity

Provide capacity hints when initializing slices with make(), particularly when appending:

data := make([]int, 0, size)

Unlike maps, slice capacity is not a hint—the compiler allocates exactly that much memory. Subsequent append() operations incur zero allocations until capacity is reached.

ApproachTime (100M iterations)
No capacity2.48s
With capacity0.21s

The capacity version is ~12x faster due to zero reallocations during append.


Pass Values

Don't pass pointers as function arguments just to save a few bytes. If a function refers to its argument x only as *x throughout, then the argument shouldn't be a pointer.

func process(s string) { // not *string — strings are small fixed-size headers
    fmt.Println(s)
}

Common pass-by-value types: string, io.Reader, small structs.

Exceptions:

  • Large structs where copying is expensive
  • Small structs that might grow in the future

String Concatenation

Choose the right strategy based on complexity:

MethodBest For
+Few strings, simple concat
fmt.SprintfFormatted output with mixed types
strings.BuilderLoop/piecemeal construction
strings.JoinJoining a slice
Backtick literalConstant multi-line text
Read references/STRING-OPTIMIZATION.md when choosing a string concatenation strategy, using strings.Builder in loops, or deciding between fmt.Sprintf and manual concatenation.

Benchmarking and Profiling

Always measure before and after optimizing. Use Go's built-in benchmark framework and profiling tools.

go test -bench=. -benchmem -count=10 ./...
Read references/BENCHMARKS.md when writing benchmarks, comparing results with benchstat, profiling with pprof, or interpreting benchmark output.
Validation: After applying optimizations, run bash scripts/bench-compare.sh to measure the actual impact. Only keep optimizations with measurable improvement.

Quick Reference

PatternBadGoodImprovement
Int to stringfmt.Sprint(n)strconv.Itoa(n)~2x faster
Repeated []byte[]byte("str") in loopConvert once outside~7x faster
Map initializationmake(map[K]V)make(map[K]V, size)Fewer allocs
Slice initializationmake([]T, 0)make([]T, 0, cap)~12x faster
Small fixed-size args*string, *io.Readerstring, io.ReaderNo indirection
Simple string joins1 + " " + s2(already good)Use + for few strings
Loop string buildRepeated +=strings.BuilderO(n) vs O(n²)

Related Skills

  • Data structures: See go-data-structures when choosing between slices, maps, and arrays, or understanding allocation semantics
  • Declaration patterns: See go-declarations when using make with capacity hints or initializing maps and slices
  • Concurrency: See go-concurrency when parallelizing work across goroutines or using sync.Pool for buffer reuse
  • Style principles: See go-style-core when deciding whether an optimization is worth the readability cost

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36.84%
按下载量换算1,355

Claude

28.54%
按下载量换算1,049

Cursor

18.78%
按下载量换算691

Gemini CLI

9.1%
按下载量换算335

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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