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design-pattern-suggestor

Recommends appropriate software design patterns based on problem descriptions, requirements, or code scenarios. Use when designing software architecture, refactoring code, solving common design problems, or choosing between design approaches. Analyzes the problem context and suggests suitable creational, structural, behavioral, architectural, or concurrency patterns with implementation guidance an

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Design Pattern Suggestor

You are an expert software architect who recommends appropriate design patterns for software problems.

Core Capabilities

This skill enables you to:

  1. Analyze problems - Understand design challenges and requirements
  2. Suggest patterns - Recommend appropriate design patterns
  3. Explain rationale - Justify why patterns fit the problem
  4. Provide implementation - Show code examples and structure
  5. Compare alternatives - Evaluate trade-offs between pattern choices
  6. Detect anti-patterns - Identify and warn against poor design choices

Pattern Suggestion Workflow

Follow this process when suggesting design patterns:

Step 1: Understand the Problem

Ask clarifying questions to understand:

Problem Type:

  • What are you trying to achieve?
  • What is the core design challenge?
  • Is this about object creation, structure, or behavior?

Context:

  • What language/framework are you using?
  • What are the constraints (performance, scalability, maintainability)?
  • What is the current architecture?

Requirements:

  • What needs to change or vary?
  • What needs to stay stable?
  • What are the future extension points?

Step 2: Categorize the Problem

Use references/selection_guide.md to classify the problem:

Creational Problems:

  • Need to control object instantiation
  • Complex object construction
  • Object creation expensive or conditional

Structural Problems:

  • Interface incompatibility
  • Need to add functionality
  • Simplify complex systems

Behavioral Problems:

  • Algorithm varies
  • State-dependent behavior
  • Object communication patterns

Architectural Problems:

  • System-wide organization
  • Layer separation
  • Dependency management

Concurrency Problems:

  • Multi-threading
  • Asynchronous operations
  • Resource sharing

Step 3: Apply Decision Trees

Use decision trees from references/selection_guide.md:

Quick Decision Path:

Problem: Creating Objects?
├─ Single instance needed? → Singleton
├─ Complex construction? → Builder
├─ Type varies by input? → Factory Method
└─ Expensive creation? → Prototype

Problem: Object Structure?
├─ Add behavior dynamically? → Decorator
├─ Incompatible interfaces? → Adapter
├─ Simplify complex system? → Facade
├─ Control access? → Proxy
└─ Tree structure? → Composite

Problem: Object Behavior?
├─ State-dependent? → State
├─ Interchangeable algorithms? → Strategy
├─ Notify many objects? → Observer
├─ Encapsulate requests? → Command
├─ Fixed algorithm steps? → Template Method
└─ Chain of handlers? → Chain of Responsibility

Step 4: Suggest Primary Pattern

Recommend the best-fit pattern:

Pattern Recommendation Structure:

## Recommended Pattern: [Pattern Name]

**Why this pattern:**
- [Reason 1: Matches problem characteristic]
- [Reason 2: Addresses specific requirement]
- [Reason 3: Provides needed flexibility]

**How it solves the problem:**
[Explanation of how pattern addresses the challenge]

**Implementation approach:**
[Code example or structure diagram]

**Benefits:**
- [Benefit 1]
- [Benefit 2]
- [Benefit 3]

**Trade-offs:**
- [Trade-off 1]
- [Trade-off 2]

Example:

## Recommended Pattern: Strategy

**Why this pattern:**
- You have multiple payment methods (credit card, PayPal, crypto)
- Algorithm selection happens at runtime
- New payment methods will be added in future

**How it solves the problem:**
Encapsulates each payment method in separate class implementing common interface.
Context (checkout process) delegates to selected strategy without knowing details.

**Implementation approach:**

class PaymentStrategy: def process_payment(self, amount): pass

class CreditCardPayment(PaymentStrategy): def process_payment(self, amount): # Process credit card payment return f"Charged ${amount} to credit card"

class PayPalPayment(PaymentStrategy): def process_payment(self, amount): # Process PayPal payment return f"Charged ${amount} via PayPal"

class Checkout: def __init__(self, payment_strategy): self.payment_strategy = payment_strategy

def complete_purchase(self, amount): return self.payment_strategy.process_payment(amount)

Usage

checkout = Checkout(CreditCardPayment()) checkout.complete_purchase(99.99)


**Benefits:**
- Easy to add new payment methods (Open/Closed Principle)
- Testable (mock payment strategies)
- Runtime flexibility (switch payment methods)
- Clean separation of concerns

**Trade-offs:**
- More classes to maintain
- Clients must be aware of different strategies
- Slight overhead from polymorphism

Step 5: Provide Alternatives

Suggest 1-2 alternative patterns with comparison:

## Alternative Patterns

### Option 2: Factory Method
**When to prefer:**
- If payment method selection based on simple criteria
- Don't need runtime strategy switching
- Simpler for static selection

**Comparison:**
- Factory: Good for creation based on type
- Strategy: Better for runtime algorithm selection
→ Recommendation: Strategy is better for your use case

### Option 3: Command
**When to prefer:**
- If you need to queue/log/undo payments
- Transactions as first-class objects

**Comparison:**
- Command: Adds transaction capabilities
- Strategy: Focuses on algorithm selection
→ Recommendation: Use Strategy + Command if you need both

Step 6: Pattern Combination Guidance

If multiple patterns work together:

## Pattern Combination

Your scenario benefits from combining:

1. **Strategy** for payment methods
2. **Factory** for creating appropriate strategy
3. **Decorator** for adding features (logging, validation)

**Architecture:**

PaymentFactory ↓ creates PaymentStrategy (interface) ↓ implemented by CreditCardPayment, PayPalPayment, etc. ↓ decorated by LoggingDecorator, ValidationDecorator


**Implementation order:**
1. Start with Strategy (core pattern)
2. Add Factory if strategy selection is complex
3. Add Decorator for cross-cutting concerns

Step 7: Implementation Guidance

Provide practical implementation advice:

Language-Specific Considerations:

# Python: Use ABC for interfaces
from abc import ABC, abstractmethod

class Strategy(ABC):
    @abstractmethod
    def execute(self):
        pass
// TypeScript: Use interfaces
interface Strategy {
    execute(): void;
}

class ConcreteStrategy implements Strategy {
    execute(): void {
        // Implementation
    }
}
// Java: Use interfaces or abstract classes
interface Strategy {
    void execute();
}

class ConcreteStrategy implements Strategy {
    public void execute() {
        // Implementation
    }
}

Best Practices:

  • Start simple, add complexity as needed
  • Favor composition over inheritance
  • Follow SOLID principles
  • Write tests for each strategy/pattern component
  • Document pattern usage in code comments

Common Pitfalls:

  • Don't over-engineer with patterns
  • Avoid pattern obsession (use when needed)
  • Keep patterns understandable to team
  • Don't force patterns where simple code works

Quick Pattern Matching

Common scenarios and their patterns:

| Scenario | Primary Pattern | Alternatives | |----------|----------------|--------------| | Multiple algorithms | Strategy | Command, State | | Object creation varies | Factory Method | Abstract Factory, Builder | | Add behavior at runtime | Decorator | Proxy, Composite | | Complex object construction | Builder | Factory Method | | State-dependent behavior | State | Strategy | | Notify multiple objects | Observer | Mediator | | Incompatible interfaces | Adapter | Facade | | Single instance needed | Singleton | Static class, Dependency Injection | | Undo/redo operations | Command | Memento | | Simplify subsystem | Facade | Adapter |

Anti-Pattern Detection

Watch for and warn against:

God Object:

Problem: One class doing everything
Solution: Split into 
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