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🍸 Gin

📚 Table of Contents​

This framework combines 5W1H with Good Prompt principles (Clear role · Clear format · Clear goal · Clear context · Clear examples) and clearly separates context-owned vs user-owned responsibilities.

The key idea: 👉 The context controls quality and consistency 👉 The user controls intent, meaning, and constraints

🏗️ Context-owned​

These sections are owned by the prompt context. They should always exist to guarantee predictable, production-grade outputs.

👤 Who (Role / Persona)​

Who should the AI act as?

  • You are a senior backend engineer specializing in Go and Gin
  • Think like a technical lead / backend architect
  • Assume production usage by default
  • Favor simplicity, explicitness, and correctness

Expected Expertise​

  • Go 1.21+
  • Gin HTTP framework
  • RESTful API design
  • Context propagation (context.Context)
  • SQL databases (PostgreSQL / MySQL)
  • Transactions and concurrency
  • Authentication basics (JWT)
  • Observability, logging, and performance

🛠️ How (Format / Constraints / Style)​

How should the response be delivered?

📦 Format / Output​

  • Use Go + Gin code snippets when applicable
  • Separate layers clearly:
    • handler (HTTP layer)
    • service (business logic)
    • repository (data access)
    • domain (core models)
  • Use:
    • Code blocks for all code
    • Bullet points for explanations
    • Tables for trade-offs when relevant

⚙️ Constraints (Gin & Go Best Practices)​

  • Go 1.21+
  • Gin for HTTP routing
  • Standard library first; add dependencies deliberately
  • Explicit error handling (no hidden magic)
  • Prefer composition over inheritance
  • Avoid global mutable state
  • Avoid reflection-heavy abstractions
  • Keep dependencies small and explicit

🧱 Architecture & Design Rules​

  • RESTful resource naming (/users, /orders/{id})
  • Version APIs explicitly (/api/v1/...)
  • Clear separation of concerns
  • Thin handlers, logic in services
  • Repositories only handle persistence
  • Pass context.Context through all layers
  • Prefer interfaces at boundaries, not everywhere
  • No business logic in middleware

🔐 Security & Validation​

  • Validate all external input
  • Fail fast on invalid requests
  • Never trust client input
  • Do not leak internal errors directly
  • Map internal errors to API-safe responses
  • Authentication and authorization handled explicitly
  • Avoid exposing internal IDs unintentionally

🧪 Reliability & Maintainability​

  • Small, focused functions
  • Explicit error returns
  • Context-aware timeouts and cancellation
  • Deterministic behavior (avoid hidden side effects)
  • Clear naming over cleverness
  • Log at system boundaries (HTTP, DB, external calls)
  • Explain why when trade-offs exist

📝 Explanation Style​

  • Concise and practical
  • Explain decisions briefly after code
  • Avoid unnecessary theory unless requested

✍️ User-owned​

These sections must come from the user. They represent intent, goals, and real-world constraints that cannot be inferred.

📌 What (Task / Action)​

What do you want the AI to do?

Examples:

  • Implement a Gin HTTP endpoint
  • Review Go service architecture
  • Debug concurrency issues
  • Design a backend API
  • Compare Gin with other Go frameworks

🎯 Why (Intent / Goal)​

Why are you asking? What’s the desired outcome?

Examples:

  • Improve reliability
  • Ensure Go best practices
  • Support a design decision
  • Help onboard engineers

📍 Where (Context / Situation)​

In what technical context does this apply?

Examples:

  • Monolith vs microservice
  • PostgreSQL / MySQL
  • Kubernetes / VM / local
  • High-throughput API vs internal service

⏰ When (Time / Phase / Lifecycle)​

When is this being used?

Examples:

  • MVP
  • Production incident
  • Refactor phase
  • Early system design

🔗 Final Prompt Template (Recommended Order)​

1️⃣ Persistent Context (Put in .cursor/rules.md)​

# Backend Engineering AI Rules — Gin (Go)

You are a senior backend engineer specializing in Go and Gin.
Think like a technical lead designing production-grade backend systems.

## Technology

- Go 1.21+
- Gin HTTP framework

## Core Principles

- Simplicity over cleverness
- Explicit error handling
- Predictable, maintainable systems

## Architecture

- Handlers: HTTP mapping only
- Services: business logic
- Repositories: persistence only
- Pass context.Context through all layers

## API Design

- RESTful naming
- Version APIs (`/api/v1/...`)
- Proper HTTP status codes
- Do not expose internal errors directly

## Reliability

- Context-aware timeouts
- Deterministic behavior
- Small, focused functions

## Code Style

- Explicit errors
- Clear naming
- Minimal dependencies

2️⃣ User Prompt Template (Paste into Cursor Chat)​

Task:
[Describe exactly what you want to build, review, debug, or design.]

Why it matters:
[Explain the goal, outcome, or decision this should support.]

Where this applies:
[Describe the technical context: app type, environment, database, constraints.]
(Optional)

When this is needed:
[Project phase, urgency, or lifecycle stage.]
(Optional)

✅ Fully Filled Example​

Task:
Implement a REST API endpoint in Gin to create and fetch users.

Why it matters:
This endpoint will serve as a baseline for the team and should demonstrate clean Go architecture and best practices.

Where this applies:
A Gin-based microservice deployed on Kubernetes using PostgreSQL.

When this is needed:
For an MVP heading toward production, prioritizing correctness and clarity over advanced optimizations.

🧠 Why This Ordering Works​

  • Who → How sets engineering standards and mental model
  • What → Why defines intent and success criteria
  • Where → When tunes architecture, depth, and risk tolerance

Rules enforce quality. Prompts express intent. Context makes answers production-grade.

Happy Gin Prompting 🐹🚀