Which concurrency patterns are supported?

It supports several core patterns including Worker Pools, Fan-out/Fan-in, Pipelines, Semaphores, and Rate Limiters.

How does it handle goroutine leaks?

The skill enforces Context-aware patterns to ensure that all goroutines are properly cancelled or timed out, preventing resource leaks in production.

Does this skill help prevent Go data races?

Yes, it provides idiomatic patterns for sync.Mutex and sync.RWMutex usage, along with debugging commands to run the Go race detector.

Does it support structured error handling in goroutines?

Yes, it utilizes the errgroup package and context-based error propagation to ensure errors in background tasks are correctly caught and handled.

Can I configure the number of concurrent workers?

Yes, the skill includes a 'workers' parameter that allows you to specify the concurrency level, defaulting to the available CPU count.

Go Concurrency Master

Name: Go Concurrency Master
Author: pluginagentmarketplace

bypluginagentmarketplace

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API Development

Implements production-grade Go concurrency patterns including worker pools, channels, and sync primitives for safe parallel programming.

About

The Go Concurrency skill empowers Claude to architect and implement sophisticated multi-threaded applications using idiomatic Go patterns. It provides standardized templates for complex synchronization tasks such as worker pools, fan-out/fan-in pipelines, and rate limiting while ensuring strict adherence to thread-safety best practices. By incorporating context-aware goroutines and robust error handling via error groups, this skill helps developers avoid common pitfalls like deadlocks, goroutine leaks, and data races, resulting in highly scalable and performant backend services.

Key Features

Built-in rate limiting and exponential backoff retry logic
Thread-safe state management using sync primitives and Mutex patterns
1 GitHub stars
Standardized worker pool and pipeline implementation templates
Context-aware goroutine management for graceful cancellation
Automated troubleshooting guides for deadlocks and race conditions

Use Cases

Implementing rate-limited API consumers and concurrent web scrapers
Building high-performance data processing pipelines and stream handlers
Developing thread-safe backend services with complex shared state requirements

About

Key Features

Built-in rate limiting and exponential backoff retry logic
Thread-safe state management using sync primitives and Mutex patterns
1 GitHub stars
Standardized worker pool and pipeline implementation templates
Context-aware goroutine management for graceful cancellation
Automated troubleshooting guides for deadlocks and race conditions

Use Cases

Implementing rate-limited API consumers and concurrent web scrapers
Building high-performance data processing pipelines and stream handlers
Developing thread-safe backend services with complex shared state requirements