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Agent Skill · 开发

go-concurrency-patterns(Go 并发模式)

go-concurrency-patterns 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 Codex、Claude、Cursor、Gemini CLI 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。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。

go-concurrency-patterns 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证为 MIT,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 296。

总安装 137,808周安装 5,762GitHub Stars 34,465下载 48,256核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

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-concurrency-patterns(Go 并发模式)
来源仓库:https://github.com/wshobson/agents
仓库路径:skills/go-concurrency-patterns
安装命令:
npx skills add https://github.com/wshobson/agents --skill go-concurrency-patterns
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/wshobson/agents --skill go-concurrency-patterns

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

Go 并发的生产模式,包括 goroutine、通道、同步原语和上下文管理。

涵盖核心原语:goroutines、channels、select、sync.Mutex、sync.WaitGroup 和 context.Context,并为每个原语提供实际示例 包括七种经过实战检验的模式:工作池、扇出/扇入管道、信号量有界并发、正常关闭、错误组、并发映射和选择超时 通过命令行标志和最佳实践提供竞争检测指导,以避免 Goroutine 泄漏和通道关闭不当等常见陷阱 演示所有示例中基于上下文的取消、截止日期管理和正确的清理模式

来源仓库内路径:skills/go-concurrency-patterns

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/wshobson/agents --skill go-concurrency-pattern…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

go-concurrency-patterns 怎么安装?

在终端执行 npx skills add https://github.com/wshobson/agents --skill go-concurrency-patterns。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

go-concurrency-patterns 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

go-concurrency-patterns 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/wshobson/agents --skill go-concurrency-patterns;npx skills add wshobson/agents --skill "go-concurrency-patterns" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

go-concurrency-patterns 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

go-concurrency-patterns 用的人多吗?

公开数据是累计安装 137,808 次,近一周安装 5,762 次,下载 48,256 次,GitHub 34,465 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

go-concurrency-patterns 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
go-concurrency-patterns

Go 并发模式 · 本页

137,80834,465执行命令MIT通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Go Concurrency Patterns

Production patterns for Go concurrency including goroutines, channels, synchronization primitives, and context management.

When to Use This Skill

  • Building concurrent Go applications
  • Implementing worker pools and pipelines
  • Managing goroutine lifecycles
  • Using channels for communication
  • Debugging race conditions
  • Implementing graceful shutdown

Core Concepts

1. Go Concurrency Primitives

PrimitivePurpose
goroutineLightweight concurrent execution
channelCommunication between goroutines
selectMultiplex channel operations
sync.MutexMutual exclusion
sync.WaitGroupWait for goroutines to complete
context.ContextCancellation and deadlines

2. Go Concurrency Mantra

Don't communicate by sharing memory;
share memory by communicating.

Quick Start

package main

import (
    "context"
    "fmt"
    "sync"
    "time"
)

func main() {
    ctx, cancel := context.WithTimeout(context.Background(), 5*time.Second)
    defer cancel()

    results := make(chan string, 10)
    var wg sync.WaitGroup

    // Spawn workers
    for i := 0; i < 3; i++ {
        wg.Add(1)
        go worker(ctx, i, results, &wg)
    }

    // Close results when done
    go func() {
        wg.Wait()
        close(results)
    }()

    // Collect results
    for result := range results {
        fmt.Println(result)
    }
}

func worker(ctx context.Context, id int, results chan<- string, wg *sync.WaitGroup) {
    defer wg.Done()

    select {
    case <-ctx.Done():
        return
    case results <- fmt.Sprintf("Worker %d done", id):
    }
}

Patterns

Pattern 1: Worker Pool

package main

import (
    "context"
    "fmt"
    "sync"
)

type Job struct {
    ID   int
    Data string
}

type Result struct {
    JobID int
    Output string
    Err   error
}

func WorkerPool(ctx context.Context, numWorkers int, jobs <-chan Job) <-chan Result {
    results := make(chan Result, len(jobs))

    var wg sync.WaitGroup
    for i := 0; i < numWorkers; i++ {
        wg.Add(1)
        go func(workerID int) {
            defer wg.Done()
            for job := range jobs {
                select {
                case <-ctx.Done():
                    return
                default:
                    result := processJob(job)
                    results <- result
                }
            }
        }(i)
    }

    go func() {
        wg.Wait()
        close(results)
    }()

    return results
}

func processJob(job Job) Result {
    // Simulate work
    return Result{
        JobID:  job.ID,
        Output: fmt.Sprintf("Processed: %s", job.Data),
    }
}

// Usage
func main() {
    ctx, cancel := context.WithCancel(context.Background())
    defer cancel()

    jobs := make(chan Job, 100)

    // Send jobs
    go func() {
        for i := 0; i < 50; i++ {
            jobs <- Job{ID: i, Data: fmt.Sprintf("job-%d", i)}
        }
        close(jobs)
    }()

    // Process with 5 workers
    results := WorkerPool(ctx, 5, jobs)

    for result := range results {
        fmt.Printf("Result: %+v\n", result)
    }
}

Pattern 2: Fan-Out/Fan-In Pipeline

package main

import (
    "context"
    "sync"
)

// Stage 1: Generate numbers
func generate(ctx context.Context, nums ...int) <-chan int {
    out := make(chan int)
    go func() {
        defer close(out)
        for _, n := range nums {
            select {
            case <-ctx.Done():
                return
            case out <- n:
            }
        }
    }()
    return out
}

// Stage 2: Square numbers (can run multiple instances)
func square(ctx context.Context, in <-chan int) <-chan int {
    out := make(chan int)
    go func() {
        defer close(out)
        for n := range in {
            select {
            case <-ctx.Done():
                return
            case out <- n * n:
            }
        }
    }()
    return out
}

// Fan-in: Merge multiple channels into one
func merge(ctx context.Context, cs ...<-chan int) <-chan int {
    var wg sync.WaitGroup
    out := make(chan int)

    // Start output goroutine for each input channel
    output := func(c <-chan int) {
        defer wg.Done()
        for n := range c {
            select {
            case <-ctx.Done():
                return
            case out <- n:
            }
        }
    }

    wg.Add(len(cs))
    for _, c := range cs {
        go output(c)
    }

    // Close out after all inputs are done
    go func() {
        wg.Wait()
        close(out)
    }()

    return out
}

func main() {
    ctx, cancel := context.WithCancel(context.Background())
    defer cancel()

    // Generate input
    in := generate(ctx, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10)

    // Fan out to multiple squarers
    c1 := square(ctx, in)
    c2 := square(ctx, in)
    c3 := square(ctx, in)

    // Fan in results
    for result := range merge(ctx, c1, c2, c3) {
        fmt.Println(result)
    }
}

Pattern 3: Bounded Concurrency with Semaphore

package main

import (
    "context"
    "fmt"
    "golang.org/x/sync/semaphore"
    "sync"
)

type RateLimitedWorker struct {
    sem *semaphore.Weighted
}

func NewRateLimitedWorker(maxConcurrent int64) *RateLimitedWorker {
    return &RateLimitedWorker{
        sem: semaphore.NewWeighted(maxConcurrent),
    }
}

func (w *RateLimitedWorker) Do(ctx context.Context, tasks []func() error) []error {
    var (
        wg     sync.WaitGroup
        mu     sync.Mutex
        errors []error
    )

    for _, task := range tasks {
        // Acquire semaphore (blocks if at limit)
        if err := w.sem.Acquire(ctx, 1); err != nil {
            return []error{err}
        }

        wg.Add(1)
        go func(t func() error) {
            defer wg.Done()
            defer w.sem.Release(1)

            if err := t(); err != nil {
                mu.Lock()
                errors = append(errors, err)
                mu.Unlock()
            }
        }(task)
    }

    wg.Wait()
    return errors
}

// Alternative: Channel-based semaphore
type Semaphore chan struct{}

func NewSemaphore(n int) Semaphore {
    return make(chan struct{}, n)
}

func (s Semaphore) Acquire() {
    s <- struct{}{}
}

func (s Semaphore) Release() {
    <-s
}

Pattern 4: Graceful Shutdown

package main

import (
    "context"
    "fmt"
    "os"
    "os/signal"
    "sync"
    "syscall"
    "time"
)

type Server struct {
    shutdown chan struct{}
    wg       sync.WaitGroup
}

func NewServer() *Server {
    return &Server{
        shutdown: make(chan struct{}),
    }
}

func (s *Server) Start(ctx context.Context) {
    // Start workers
    for i := 0; i < 5; i++ {
        s.wg.Add(1)
        go s.worker(ctx, i)
    }
}

func (s *Server) worker(ctx context.Context, id int) {
    defer s.wg.Done()
    defer fmt.Printf("Worker %d stopped\n", id)

    ticker := time.NewTicker(time.Second)
    defer ticker.Stop()

    for {
        select {
        case <-ctx.Done():
            // Cleanup
            fmt.Printf("Worker %d cleaning up...\n", id)
            time.Sleep(500 * time.Millisecond) // Simulated cleanup
            return
        case <-ticker.C:
            fmt.Printf("Worker %d working...\n", id)
        }
    }
}

func (s *Server) Shutdown(timeout time.Duration) {
    // Signal shutdown
    close(s.shutdown)

    // Wait with timeout
    done := make(chan struct{})
    go func() {
        s.wg.Wait()
        close(done)
    }()

    select {
    case <-done:
        fmt.Println("Clean shutdown completed")
    case <-time.After(timeout):
        fmt.Println("Shutdown timed out, forcing exit")
    }
}

func main() {
    // Setup signal handling
    ctx, cancel := context.WithCancel(context.Background())

    sigCh := make(chan os.Signal, 1)
    signal.Notify(sigCh, syscall.SIGINT, syscall.SIGTERM)

    server := NewServer()
    server.Start(ctx)

    // Wait for signal
    sig := <-sigCh
    fmt.Printf("\nReceived signal: %v\n", sig)

    // Cancel context to stop workers
    cancel()

    // Wait for graceful shutdown
    server.Shutdown(5 * time.Second)
}

Pattern 5: Error Group with Cancellation

package main

import (
    "context"
    "fmt"
    "golang.org/x/sync/errgroup"
    "net/http"
)

func fetchAllURLs(ctx context.Context, urls []string) ([]string, error) {
    g, ctx := errgroup.WithContext(ctx)

    results := make([]string, len(urls))

    for i, url := range urls {
        i, url := i, url // Capture loop variables

        g.Go(func() error {
            req, err := http.NewRequestWithContext(ctx, "GET", url, nil)
            if err != nil {
                return fmt.Errorf("creating request for %s: %w", url, err)
            }

            resp, err := http.DefaultClient.Do(req)
            if err != nil {
                return fmt.Errorf("fetching %s: %w", url, err)
            }
            defer resp.Body.Close()

            results[i] = fmt.Sprintf("%s: %d", url, resp.StatusCode)
            return nil
        })
    }

    // Wait for all goroutines to complete or one to fail
    if err := g.Wait(); err != nil {
        return nil, err // First error cancels all others
    }

    return results, nil
}

// With concurrency limit
func fetchWithLimit(ctx context.Context, urls []string, limit int) ([]string, error) {
    g, ctx := errgroup.WithContext(ctx)
    g.SetLimit(limit) // Max concurrent goroutines

    results := make([]string, len(urls))
    var mu sync.Mutex

    for i, url := range urls {
        i, url := i, url

        g.Go(func() error {
            result, err := fetchURL(ctx, url)
            if err != nil {
                return err
            }

            mu.Lock()
            results[i] = result
            mu.Unlock()
            return nil
        })
    }

    if err := g.Wait(); err != nil {
        return nil, err
    }

    return results, nil
}

Pattern 6: Concurrent Map with sync.Map

package main

import (
    "sync"
)

// For frequent reads, infrequent writes
type Cache struct {
    m sync.Map
}

func (c *Cache) Get(key string) (interface{}, bool) {
    return c.m.Load(key)
}

func (c *Cache) Set(key string, value interface{}) {
    c.m.Store(key, value)
}

func (c *Cache) GetOrSet(key string, value interface{}) (interface{}, bool) {
    return c.m.LoadOrStore(key, value)
}

func (c *Cache) Delete(key string) {
    c.m.Delete(key)
}

// For write-heavy workloads, use sharded map
type ShardedMap struct {
    shards    []*shard
    numShards int
}

type shard struct {
    sync.RWMutex
    data map[string]interface{}
}

func NewShardedMap(numShards int) *ShardedMap {
    m := &ShardedMap{
        shards:    make([]*shard, numShards),
        numShards: numShards,
    }
    for i := range m.shards {
        m.shards[i] = &shard{data: make(map[string]interface{})}
    }
    return m
}

func (m *ShardedMap) getShard(key string) *shard {
    // Simple hash
    h := 0
    for _, c := range key {
        h = 31*h + int(c)
    }
    return m.shards[h%m.numShards]
}

func (m *ShardedMap) Get(key string) (interface{}, bool) {
    shard := m.getShard(key)
    shard.RLock()
    defer shard.RUnlock()
    v, ok := shard.data[key]
    return v, ok
}

func (m *ShardedMap) Set(key string, value interface{}) {
    shard := m.getShard(key)
    shard.Lock()
    defer shard.Unlock()
    shard.data[key] = value
}

Pattern 7: Select with Timeout and Default

func selectPatterns() {
    ch := make(chan int)

    // Timeout pattern
    select {
    case v := <-ch:
        fmt.Println("Received:", v)
    case <-time.After(time.Second):
        fmt.Println("Timeout!")
    }

    // Non-blocking send/receive
    select {
    case ch <- 42:
        fmt.Println("Sent")
    default:
        fmt.Println("Channel full, skipping")
    }

    // Priority select (check high priority first)
    highPriority := make(chan int)
    lowPriority := make(chan int)

    for {
        select {
        case msg := <-highPriority:
            fmt.Println("High priority:", msg)
        default:
            select {
            case msg := <-highPriority:
                fmt.Println("High priority:", msg)
            case msg := <-lowPriority:
                fmt.Println("Low priority:", msg)
            }
        }
    }
}

Race Detection

# Run tests with race detector
go test -race ./...

# Build with race detector
go build -race .

# Run with race detector
go run -race main.go

Best Practices

Do's

  • Use context - For cancellation and deadlines
  • Close channels - From sender side only
  • Use errgroup - For concurrent operations with errors
  • Buffer channels - When you know the count
  • Prefer channels - Over mutexes when possible

Don'ts

  • Don't leak goroutines - Always have exit path
  • Don't close from receiver - Causes panic
  • Don't use shared memory - Unless necessary
  • Don't ignore context cancellation - Check ctx.Done()
  • Don't use time.Sleep for sync - Use proper primitives

平台分布

Claude Code

28.63%
按下载量换算13,816

Cursor

22.11%
按下载量换算10,669

OpenCode

16.23%
按下载量换算7,832

Gemini CLI

10.99%
按下载量换算5,303

Antigravity

6.76%
按下载量换算3,262

Codex

3.53%
按下载量换算1,703

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/wshobson/agents --skill go-concurrency-patterns;npx skills add wshobson/agents --skill "go-concurrency-patterns" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。

继续浏览同类 Skills