Code Designing

Domain type design and architectural planning for Go code. Use when planning new features or identifying need for new types during refactoring.

When to Use

• Planning a new feature (before writing code)
• Refactoring reveals need for new types (complexity extraction)
• Linter failures suggest types should be introduced
• When you need to think through domain modeling

Purpose

Design clean, self-validating types that:

• Prevent primitive obsession
• Ensure type safety
• Make validation explicit
• Follow vertical slice architecture

Workflow

0. Architecture Pattern Analysis (FIRST STEP)

Default: Always use vertical slice architecture (feature-first, not layer-first).

Scan codebase structure:

• Vertical slicing: internal/feature/{handler,service,repository,models}.go ✅
• Horizontal layering: internal/{handlers,services,domain}/feature.go ⚠️

Decision Flow:

1. Pure vertical → Continue pattern, implement as internal/[new-feature]/
2. Pure horizontal → Propose: Start migration with docs/architecture/vertical-slice-migration.md, implement new feature as first vertical slice
3. Mixed (migrating) → Check for migration docs, continue pattern as vertical slice

Always ask user approval with options:

• Option A: Vertical slice (recommended for cohesion/maintainability)
• Option B: Match existing pattern (if time-constrained)
• Acknowledge: Time pressure, team decisions, consistency needs are valid

If migration needed, create/update docs/architecture/vertical-slice-migration.md:

# Vertical Slice Migration Plan
## Current State: [horizontal/mixed]
## Target: Vertical slices in internal/[feature]/
## Strategy: New features vertical, migrate existing incrementally
## Progress: [x] [new-feature] (this PR), [ ] existing features

See reference.md section #3 for detailed patterns.

1. Understand Domain

• What is the problem domain?
• What are the main concepts/entities?
• What are the invariants and rules?
• How does this fit into existing architecture?

2. Identify Core Types

Ask for each concept:

• Is this currently a primitive (string, int, float)?
• Does it have validation rules?
• Does it have behavior beyond simple data?
• Is it used across multiple places?

If yes to any → Consider creating a type

3. Design Self-Validating Types

For each type:

// Type definition
type TypeName underlyingType

// Validating constructor
func NewTypeName(input underlyingType) (TypeName, error) {
    // Validate input
    if /* validation fails */ {
        return zero, errors.New("why it failed")
    }
    return TypeName(input), nil
}

// Methods on type (if behavior needed)
func (t TypeName) SomeMethod() result {
    // Type-specific logic
}

4. Plan Package Structure

• Vertical slices: Group by feature, not layer
• Each feature gets its own package
• Within package: separate by role (service, repository, handler)

Good structure:

user/
├── user.go          # Domain types
├── service.go       # Business logic
├── repository.go    # Persistence
└── handler.go       # HTTP/API

Bad structure:

domain/user.go
services/user_service.go
repository/user_repository.go

5. Design Orchestrating Types

For types that coordinate others:

• Make fields private
• Validate dependencies in constructor
• No nil checks in methods (constructor guarantees validity)

type Service struct {
    repo        Repository  // private
    notifier    Notifier    // private
}

func NewService(repo Repository, notifier Notifier) (*Service, error) {
    if repo == nil {
        return nil, errors.New("repo required")
    }
    if notifier == nil {
        return nil, errors.New("notifier required")
    }
    return &Service{
        repo:     repo,
        notifier: notifier,
    }, nil
}

// Methods can trust fields are valid
func (s *Service) DoSomething() error {
    // No nil checks needed
    return s.repo.Save(...)
}

6. Review Against Principles

Check design against (see reference.md):

• No primitive obsession
• Types are self-validating
• Vertical slice architecture
• Types designed around intent, not just shape
• Clear separation of concerns

Output Format

After design phase:

🎨 DESIGN PLAN

Feature: [Feature Name]

Core Domain Types:
✅ UserID (string) - Self-validating, prevents empty IDs
✅ Email (string) - Self-validating, RFC 5322 validation
✅ Age (int) - Self-validating, range 0-150

Orchestrating Types:
✅ UserService - Coordinates user operations
   Dependencies: Repository, Notifier
   Methods: CreateUser, GetUser, UpdateUser

Package Structure:
📁 user/
  ├── user.go          # UserID, Email, Age, User
  ├── service.go       # UserService
  ├── repository.go    # Repository interface + implementations
  ├── notifier.go      # Notifier interface + implementations
  └── handler.go       # HTTP handlers

Design Decisions:
- UserID is custom type to prevent passing empty/invalid IDs
- Email validation centralized in NewEmail constructor
- Vertical slice keeps all user logic in one package
- Repository as interface allows multiple backends (Postgres, in-memory for tests)

Integration Points:
- Consumed by: HTTP API (/users endpoints)
- Depends on: Database, Email service
- Events: UserCreated event published after creation

Next Steps:
1. Create types with validating constructors
2. Write unit tests for each type
3. Implement UserService
4. Write integration tests

Ready to implement? Use @testing skill for test structure.

Key Principles

See reference.md for detailed principles:

• Primitive obsession prevention (Yoke design strategy)
• Self-validating types
• Vertical slice architecture
• Types around intent and behavior, not just shape
• Single responsibility per type

Pre-Code Review Questions

Before writing code, ask:

• Can logic be moved into smaller custom types?
• Is this type designed around intent and behavior?
• Have I avoided primitive obsession?
• Is validation in the right place (constructor)?
• Does this follow vertical slice architecture?

Only after satisfactory answers, proceed to implementation.

See reference.md for complete design principles and examples.