typescript-rules

name	typescript-rules
description	Applies type safety and error handling rules. Enforces no-any policy and type guards. Use when implementing TypeScript or reviewing types.

TypeScript Development Rules

Type Safety in Backend Implementation

Type Safety in Data Flow Input Layer (unknown) -> Type Guard -> Business Layer (Type Guaranteed) -> Output Layer (Serialization)

Backend-Specific Type Scenarios:

• API Communication: Always receive responses as unknown, validate with type guards
• Form Input: External input as unknown, type determined after validation
• Legacy Integration: Stepwise assertion like window as unknown as LegacyWindow
• Test Code: Always define types for mocks, utilize Partial<T> and vi.fn<[Args], Return>()

Coding Conventions

Class Usage Criteria

• Recommended: Implementation with Functions and Interfaces
  • Rationale: Improves testability and flexibility of function composition
• Classes Allowed:
  • Framework requirements (NestJS Controller/Service, TypeORM Entity, etc.)
  • Custom error class definitions
  • When state and business logic are tightly coupled (e.g., ShoppingCart, Session, StateMachine)
• Decision Criterion: If "Does this data have behavior?" is Yes, consider using a class

  // Functions and interfaces
  interface UserService { create(data: UserData): User }
  const userService: UserService = { create: (data) => {...} }
  

Function Design

• 0-2 parameters maximum: Use object for 3+ parameters

  // Object parameter
  function createUser({ name, email, role }: CreateUserParams) {}
  

Dependency Injection

• Inject external dependencies as parameters: Ensure testability and modularity

  // Receive dependency as parameter
  function createService(repository: Repository) { return {...} }
  

Asynchronous Processing

• Promise Handling: Always use async/await
• Error Handling: Always handle with try-catch
• Type Definition: Explicitly define return value types (e.g., Promise<Result>)

Format Rules

• Semicolon omission (follow Biome settings)
• Types in PascalCase, variables/functions in camelCase
• Imports use absolute paths (src/)

Clean Code Principles

• Delete unused code immediately
• Delete debug console.log()
• No commented-out code (manage history with version control)
• Comments explain "why" (not "what")

Error Handling

Absolute Rule: Error suppression prohibited. All errors must have log output and appropriate handling.

Fail-Fast Principle: Fail quickly on errors to prevent continued processing in invalid states

// Prohibited: Unconditional fallback
catch (error) {
  return defaultValue // Hides error
}

// Required: Explicit failure
catch (error) {
  logger.error('Processing failed', error)
  throw error // Handle appropriately at higher layer
}

Result Type Pattern: Express errors with types for explicit handling

type Result<T, E> = { ok: true; value: T } | { ok: false; error: E }

// Example: Express error possibility with types
function parseUser(data: unknown): Result<User, ValidationError> {
  if (!isValid(data)) return { ok: false, error: new ValidationError() }
  return { ok: true, value: data as User }
}

Custom Error Classes

export class AppError extends Error {
  constructor(message: string, public readonly code: string, public readonly statusCode = 500) {
    super(message)
    this.name = this.constructor.name
  }
}
// Purpose-specific: ValidationError(400), BusinessRuleError(400), DatabaseError(500), ExternalServiceError(502)

Layer-Specific Error Handling (Backend)

• API Layer: Convert to HTTP response, log output excluding sensitive information
• Service Layer: Detect business rule violations, propagate AppError as-is
• Repository Layer: Convert technical errors to domain errors

Structured Logging and Sensitive Information Protection Never include sensitive information (password, token, apiKey, secret, creditCard) in logs

Asynchronous Error Handling

• Global handler setup mandatory: unhandledRejection, uncaughtException
• Use try-catch with all async/await
• Always log and re-throw errors

Performance Optimization

• Streaming Processing: Process large datasets with streams
• Memory Leak Prevention: Explicitly release unnecessary objects