Can this skill help debug race conditions?

Yes, it provides best-practice patterns for synchronization using Mutexes and sync.Map to ensure thread safety and avoid data races.

What Go concurrency patterns are supported?

The skill includes patterns for Worker Pools, Fan-Out/Fan-In pipelines, Bounded Concurrency using Semaphores, Graceful Shutdown, and Error Groups.

Does it support context-based cancellation?

Absolutely. All patterns are designed with context.Context support to handle timeouts, deadlines, and graceful cancellations across goroutine hierarchies.

Is this skill suitable for production Go services?

Yes, the patterns follow the 'share memory by communicating' mantra and use idiomatic Go primitives suitable for high-scale production environments.

Go Concurrency Patterns

Name: Go Concurrency Patterns
Author: wshobson

bywshobson

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23,194

API Development

Implements production-grade Go concurrency patterns including worker pools, pipelines, and graceful shutdowns.

About

This skill empowers Claude to architect and debug high-performance Go applications using advanced concurrency primitives. It provides standardized, battle-tested implementations for common patterns like worker pools, fan-in/fan-out pipelines, and robust error handling with errgroups. By leveraging goroutines, channels, and context management, it ensures your concurrent Go code is thread-safe, efficient, and free of race conditions, making it indispensable for building scalable backend services and data processing systems.

Key Features

Graceful shutdown patterns for long-running services and microservices
23,194 GitHub stars
Advanced synchronization using WaitGroups, Mutexes, and Semaphores
Standardized Worker Pool and Fan-Out/Fan-In pipeline implementations
Thread-safe data structures including sharded and sync.Map implementations
Context-aware goroutine management for reliable cancellation and timeouts

Use Cases

Implementing rate-limited API clients and concurrent web scrapers
Building high-throughput data processing pipelines for large datasets
Managing background worker lifecycles in cloud-native Go applications

About

Key Features

Graceful shutdown patterns for long-running services and microservices
23,194 GitHub stars
Advanced synchronization using WaitGroups, Mutexes, and Semaphores
Standardized Worker Pool and Fan-Out/Fan-In pipeline implementations
Thread-safe data structures including sharded and sync.Map implementations
Context-aware goroutine management for reliable cancellation and timeouts

Use Cases

Implementing rate-limited API clients and concurrent web scrapers
Building high-throughput data processing pipelines for large datasets
Managing background worker lifecycles in cloud-native Go applications