go-concurrency-patterns

Name: go-concurrency-patterns
Availability: InStock
Author: ai-safeter

Structure Go concurrency with worker pools, pipelines, and graceful shutdown.

10|Updated May 20, 2026

Search Tags:#context #concurrency #go #channels #pipelines #goroutines #worker pool

Ready to run

npx skills add https://github.com/AI-Safeter/antigravity-cli-plugin --skill go-concurrency-patterns-ai-safeter

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: go-concurrency-patterns
Source: https://github.com/AI-Safeter/antigravity-cli-plugin/tree/main/plugins/go-concurrency-patterns
Command: npx skills add https://github.com/AI-Safeter/antigravity-cli-plugin --skill go-concurrency-patterns-ai-safeter

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Go applications often struggle with safe and scalable concurrency. This Skill provides proven patterns to structure goroutines, channels, and synchronization primitives to avoid data races and resource leaks.

Core Features & Use Cases

Worker Pool: coordinate a pool of workers to process jobs concurrently with controlled concurrency.
Fan-Out/Fan-In: route data through multiple stages and merge results with proper synchronization.
Graceful Shutdown: implement clean termination and resource cleanup on cancellation or signals.
Error Handling: use context and errgroup to propagate failures and cancel remaining work.

Quick Start

Review the Go Concurrency Patterns playbook and integrate the worker pool and pipeline designs into your Go project.

Frequently Asked Questions about go-concurrency-patterns

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I prevent race conditions and resource leaks when structuring Go concurrency?▼

Structuring Go concurrency safely requires repeatable patterns using context, errgroup, and channels. These primitives coordinate multiple goroutines, enforce proper synchronization, and prevent race conditions and resource leaks.

What is the best way to implement a worker pool in Go with controlled concurrency?▼

Implementing a Go worker pool involves coordinating a fixed number of goroutines to process jobs concurrently. This pattern provides controlled concurrency, routing data safely through channels to process jobs without exhausting resources.

How do I handle graceful shutdown and clean termination across multiple goroutines?▼

Graceful shutdown in Go uses context for cancellation and signals to trigger clean termination across multiple goroutines. This pattern enforces proper cleanup of resources and stops workers safely during cancellation.

How do I propagate errors and cancel remaining work in concurrent Go pipelines?▼

Propagating errors and canceling remaining work in Go pipelines requires using context and errgroup. This approach routes data through multiple stages, merges results, and cancels remaining goroutines on failure.

Does this Go concurrency approach work for fan-out and fan-in data routing?▼

Yes, this approach supports fan-out and fan-in data routing in Go. It routes data through multiple concurrent stages and merges results with proper synchronization to handle scaled workloads.

Why do my concurrent goroutines deadlock or leak resources during execution?▼

Goroutines deadlock or leak resources without proper synchronization and cleanup patterns. Using context, errgroup, and channels correctly enforces best practices that reduce deadlocks and prevent resource leaks during execution.