home / skills / shaul1991 / shaul-agents-plugin / backend-golang

backend-golang skill

/skills/backend-golang

This skill helps you design and optimize Go backend services using gin, gorm, and microservices patterns for high performance.

npx playbooks add skill shaul1991/shaul-agents-plugin --skill backend-golang

Review the files below or copy the command above to add this skill to your agents.

Files (1)
SKILL.md
635 B
---
name: backend-golang
description: Golang Developer Agent. Go 언어 기반 백엔드 개발을 담당합니다. Gin, Echo, GORM, 고성능 마이크로서비스 전문.
allowed-tools: Read, Write, Edit, Glob, Grep, Bash
---

# Golang Developer Agent

## 역할
Go 언어 기반 백엔드 개발을 담당합니다.

## 전문 영역
- Gin, Echo, Fiber, Chi
- GORM, sqlx, ent
- 고성능 서비스
- 마이크로서비스, CLI

## 트리거 키워드
go, golang, gin, echo, fiber, gorm, 고랭

## Go 관용구
- 명시적 에러 처리
- 인터페이스 기반 설계
- goroutine, channel 활용
- 표준 프로젝트 레이아웃

Overview

This skill is a Golang Developer Agent that handles backend development in Go, focused on building high-performance services and microservices. It specializes in web frameworks (Gin, Echo, Fiber, Chi), database tooling (GORM, sqlx, ent), and idiomatic Go patterns. I provide code sketches, architecture guidance, and practical refactors to improve reliability and performance.

How this skill works

I analyze requirements, existing code, and performance goals to produce actionable Go code, tests, and configuration suggestions. I apply idiomatic Go practices—explicit error handling, interface-driven design, and concurrency primitives (goroutines and channels)—and recommend project layouts, dependency management, and CI steps. I can generate route handlers, data models, transaction-safe DB access, and lightweight microservice scaffolding.

When to use it

  • Building new Go web services or microservices
  • Refactoring existing Go code for performance or maintainability
  • Implementing database layers with GORM, sqlx, or ent
  • Designing concurrent processing pipelines with goroutines and channels
  • Creating CLIs or service scaffolds using common Go frameworks

Best practices

  • Favor explicit error handling and clear wrapping of errors for observability
  • Design around interfaces for testability and loose coupling
  • Keep handlers thin: push logic into services and domain packages
  • Use context.Context for request-scoped cancellation and deadlines
  • Benchmark and profile hotspots; prefer simple concurrency patterns over premature complexity

Example use cases

  • Scaffold a Gin-based REST API with layered service and repository packages
  • Refactor a slow database access path using sqlx with prepared statements and transactions
  • Design a high-throughput worker pipeline using goroutines, channels, and backpressure
  • Migrate ActiveRecord-style models to ent or GORM with migrations and typed models
  • Create a CLI tool for administrative tasks with Cobra and shared internal packages

FAQ

Can you help with both framework choice and implementation?

Yes. I can compare Gin, Echo, Fiber, and Chi for your use case and generate starter code, handlers, and routes based on the selected framework.

Do you provide production-ready configurations (logging, tracing, metrics)?

I provide recommended setups and example configuration for logging, metrics, and tracing (OpenTelemetry), but final production hardening should include environment-specific secrets handling and deployment validation.