frontend-ai-guide

name: frontend-ai-guide description: Frontend-specific technical decision criteria, anti-patterns, debugging techniques, and quality check workflow. Use when making frontend technical decisions or performing quality assurance.

AI Developer Guide - Technical Decision Criteria and Anti-pattern Collection (Frontend)

Technical Anti-patterns (Red Flag Patterns)

Immediately stop and reconsider design when detecting the following patterns:

Code Quality Anti-patterns

1. Writing similar code 3 or more times - Violates Rule of Three
2. Multiple responsibilities mixed in a single component - Violates Single Responsibility Principle (SRP)
3. Defining same content in multiple components - Violates DRY principle
4. Making changes without checking dependencies - Potential for unexpected impacts
5. Disabling code with comments - Should use version control
6. Error suppression - Hiding problems creates technical debt
7. Excessive use of type assertions (as) - Abandoning type safety
8. Prop drilling through 3+ levels - Should use Context API or state management
9. Massive components (300+ lines) - Split into smaller components

Design Anti-patterns

• "Make it work for now" thinking - Accumulation of technical debt
• Patchwork implementation - Unplanned additions to existing components
• Optimistic implementation of uncertain technology - Designing unknown elements assuming "it'll probably work"
• Symptomatic fixes - Surface-level fixes that don't solve root causes
• Unplanned large-scale changes - Lack of incremental approach

Fallback Design Principles

Core Principle: Fail-Fast

Design philosophy that prioritizes improving primary code reliability over fallback implementations.

Criteria for Fallback Implementation

• Fallback rule: Implement fallbacks only when explicitly defined in Design Doc
• Layer Responsibilities:
  • Component Layer: Use Error Boundary for error handling
  • Hook Layer: Implement decisions based on business requirements

Detection of Excessive Fallbacks

• Require design review when writing the 3rd catch statement in the same feature
• Verify Design Doc definition before implementing fallbacks
• Properly log errors and make failures explicit

Rule of Three - Criteria for Code Duplication

How to handle duplicate code based on Martin Fowler's "Refactoring":

Criteria for Commonalization

Cases for Commonalization

• Business logic duplication
• Complex processing algorithms
• Component patterns (form fields, cards, etc.)
• Custom hooks
• Validation rules

Cases to Avoid Commonalization

• Accidental matches (coincidentally same code)
• Possibility of evolving in different directions
• Significant readability decrease from commonalization
• Simple helpers in test code

Implementation Example

// Immediate commonalization on 1st duplication
function UserEmailInput() { /* ... */ }
function ContactEmailInput() { /* ... */ }

// Commonalize on 3rd occurrence
function EmailInput({ context }: { context: 'user' | 'contact' | 'admin' }) { /* ... */ }

Common Failure Patterns and Avoidance Methods

Pattern 1: Error Fix Chain

Symptom: Fixing one error causes new errors Cause: Surface-level fixes without understanding root cause Avoidance: Identify root cause with 5 Whys before fixing

Pattern 2: Abandoning Type Safety

Symptom: Excessive use of any type or as Cause: Impulse to avoid type errors Avoidance: Handle safely with unknown type and type guards

Pattern 3: Implementation Without Sufficient Testing

Symptom: Many bugs after implementation Cause: Ignoring Red-Green-Refactor process Avoidance: Always start with failing tests

Pattern 4: Ignoring Technical Uncertainty

Symptom: Frequent unexpected errors when introducing new technology Cause: Assuming "it should work according to official documentation" without prior investigation Avoidance:

• Record certainty evaluation at the beginning of task files

  Certainty: low (Reason: new experimental feature with limited production examples)
  Exploratory implementation: true
  Fallback: use established patterns
  

• For low certainty cases, create minimal verification code first

Pattern 5: Insufficient Existing Code Investigation

Symptom: Duplicate implementations, architecture inconsistency, integration failures Cause: Insufficient understanding of existing code before implementation Avoidance Methods:

• Before implementation, always search for similar functionality (using domain, responsibility, component patterns as keywords)
• Similar functionality found → Use that implementation (do not create new implementation)
• Similar functionality is technical debt → Create ADR improvement proposal before implementation
• No similar functionality exists → Implement new functionality following existing design philosophy
• Record all decisions and rationale in "Existing Codebase Analysis" section of Design Doc

Debugging Techniques

1. Error Analysis Procedure

1. Read error message (first line) accurately
2. Focus on first and last of stack trace
3. Identify first line where your code appears
4. Check React DevTools for component hierarchy

2. 5 Whys - Root Cause Analysis

Symptom: Component not rendering
Why1: Props are undefined → Why2: Parent component didn't pass props
Why3: Parent using old prop names → Why4: Component interface was updated
Why5: No update to parent after refactoring
Root cause: Incomplete refactoring, missing call-site updates

3. Minimal Reproduction Code

To isolate problems, attempt reproduction with minimal code:

• Remove unrelated components
• Replace API calls with mocks
• Create minimal configuration that reproduces problem
• Use React DevTools to inspect component tree

4. Debug Log Output (temporary)

Add structured debug logs to isolate the issue, then remove them before commit (per "Delete debug console.log()" in typescript-rules):

console.log('DEBUG:', {
  context: 'user-form-submission',
  props: { email, name },
  state: currentState,
  timestamp: new Date().toISOString()
})

Quality Check Workflow

Read package.json scripts and run them with the project's package manager (packageManager field). Map the project's actual script names to the phases below — do not assume fixed names.

Phases (run in order)

1. Lint/format — the project's formatter + linter (e.g., Biome, or ESLint + Prettier)
2. Type check — type check without emit
3. Build — production build
4. Test — unit/integration tests
5. Coverage — coverage run when the task added or changed behavior

Troubleshooting

• Port already in use — stop the stale dev/preview/test process holding the port
• Stale cache — re-run with the project's fresh/clean-cache option
• Dependency errors — clean reinstall dependencies

Situations Requiring Technical Decisions

Timing of Abstraction

• Extract patterns after writing concrete implementation 3 times
• Be conscious of YAGNI, implement only currently needed features
• Prioritize current simplicity over future extensibility

Performance vs Readability

• Prioritize readability unless React DevTools Profiler identifies a measurable bottleneck (e.g., render time exceeding 16ms, unnecessary re-renders)
• Measure before optimizing with React DevTools Profiler
• Document reason with comments when optimizing

Granularity of Component/Type Definitions

• Overly detailed components/types reduce maintainability
• Design components that appropriately express UI patterns
• Use composition over inheritance

Implementation Completeness Assurance

Required Procedure for Impact Analysis

Completion Criteria: Complete all 3 stages

1. Discovery

Grep -n "ComponentName\|hookName" -o content
Grep -n "importedFunction" -o content
Grep -n "propsType\|StateType" -o content

2. Understanding

Mandatory: Read all discovered files and include necessary parts in context:

• Caller's purpose and context
• Component hierarchy
• Data flow: Props → State → Event handlers → Callbacks

3. Identification

Structured impact report (mandatory):

## Impact Analysis
### Direct Impact: ComponentA, ComponentB (with reasons)
### Indirect Impact: FeatureX, PageY (with integration paths)
### Processing Flow: Props → Render → Events → Callbacks

Important: Execute all 3 stages to completion

Unused Code Deletion Rule

When unused code is detected → Will it be used?

• Yes → Implement immediately (no deferral allowed)
• No → Delete immediately (remains in Git history)

Target: Components, hooks, utilities, documentation, configuration files

Existing Code Deletion Decision Flow

In use? No → Delete immediately (remains in Git history)
       Yes → Working? No → Delete + Reimplement
                     Yes → Fix