Intelligent Scaffolding

I'll create complete feature structures based on your project patterns, with full continuity across sessions.

Arguments: $ARGUMENTS - feature name or component to scaffold

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Token Optimization Strategy

Target: 65% reduction (3,500-5,000 → 1,200-2,000 tokens) Status: ✅ Optimized (Phase 2 Batch 3D-F, 2026-01-26)

Optimization Techniques Applied

1. Template-Based Scaffolding

• Pattern: Reuse existing feature structures as templates
• Implementation: Glob → identify similar features → copy patterns
• Savings: 70% (avoid reading documentation, reduce analysis)
• Example:

  # Instead of analyzing 20 files for patterns:
  Glob "src/features/*/index.ts" → Find 5 existing features
  Read ONLY one representative feature → Extract pattern
  Reuse pattern for new scaffolding → Generate with heredocs
  
  Before: 15,000 tokens (read all features)
  After: 1,500 tokens (read one, reuse pattern)
  Savings: 90%
  

2. Framework Detection Caching

• Pattern: Cache framework type and conventions from /understand
• Implementation: Check .claude/cache/understand/project-analysis.json
• Savings: 80% (skip framework detection)
• Cache Keys:
  • framework: React/Vue/Angular/Svelte
  • structure: File organization pattern
  • conventions: Naming and export patterns
  • testFramework: Jest/Vitest/Mocha

3. Project Conventions Caching

• Pattern: Learn and cache project-specific patterns
• Location: .claude/cache/scaffold/conventions.json
• Cached Data:

  {
    "naming": "kebab-case|PascalCase|camelCase",
    "fileStructure": "feature-folders|type-folders|flat",
    "imports": "absolute|relative",
    "exports": "named|default",
    "testLocation": "adjacent|__tests__|separate"
  }
  

• Savings: 60% (skip pattern analysis on resume)

4. Bash-Based File Generation

• Pattern: Use heredocs for creating multiple files efficiently
• Implementation:

  cat > src/features/user/index.ts <<'EOF'
  export * from './UserProfile'
  export * from './types'
  EOF
  
  cat > src/features/user/UserProfile.tsx <<'EOF'
  import React from 'react'
  // Component code generated from template
  EOF
  

• Savings: 50% (single Bash call vs multiple Write calls)
• Benefits: Atomic operations, better error handling

5. Incremental Scaffolding

• Pattern: Generate one component at a time with validation
• State Tracking: scaffold/state.json tracks completed files
• Resume Support:

  {
    "feature": "UserProfile",
    "created": ["index.ts", "types.ts", "UserProfile.tsx"],
    "pending": ["UserProfile.test.tsx", "UserProfile.stories.tsx"],
    "lastFile": "UserProfile.tsx"
  }
  

• Savings: 80% on resume (skip created files)

6. Git Diff Before Scaffolding

• Pattern: Check for existing files to avoid overwrites
• Implementation:

  git ls-files src/features/user/ # Check if feature exists
  

• Savings: 95% (immediate exit if feature exists)
• Safety: Prevents accidental overwrites

Token Cost Breakdown

Phase 1: Pattern Discovery (500-800 tokens)

• Check session: 50 tokens (Bash ls scaffold/)
• Framework detection: 100 tokens (cache hit) or 500 tokens (cache miss)
• Glob existing features: 150 tokens
• Read ONE template feature: 300-500 tokens
• Total: 600-1,200 tokens (vs 8,000 unoptimized)

Phase 2: Planning (200-400 tokens)

• Generate file list: 100 tokens (from template)
• Create plan.md: 50 tokens (Write)
• Initialize state.json: 50 tokens (Write)
• Total: 200 tokens (vs 2,000 unoptimized)

Phase 3: File Generation (500-800 tokens)

• Bash heredoc generation: 400-600 tokens (all files in one call)
• Update state.json: 50 tokens
• Git status check: 100 tokens
• Total: 550-750 tokens (vs 5,000 unoptimized)

Resume Session (300-600 tokens)

• Read state.json: 100 tokens
• Check pending files: 50 tokens
• Generate remaining files: 200-400 tokens
• Total: 350-550 tokens (vs 3,000 unoptimized)

Optimization Results

Token Savings:

• New scaffolding: 3,500-5,000 → 1,200-2,000 tokens (65% reduction)
• Resume session: 3,000-4,000 → 300-600 tokens (85% reduction)
• Small scaffold: 2,000-3,000 → 500-1,000 tokens (67% reduction)
• Average: 65% token reduction

Cost Comparison:

Before Optimization:
- New feature: 4,000 tokens × $0.003 = $0.012
- Resume: 3,500 tokens × $0.003 = $0.0105
- Annual (50 scaffolds): $0.60

After Optimization:
- New feature: 1,500 tokens × $0.003 = $0.0045
- Resume: 500 tokens × $0.003 = $0.0015
- Annual (50 scaffolds): $0.21

Savings: $0.39/year per developer (65% reduction)

Caching Strategy

Cache Locations:

• Session state: scaffold/ in project root
  • plan.md: Scaffolding plan and file list
  • state.json: Progress tracking and created files
• Framework cache: .claude/cache/understand/
  • Shared with /understand, /implement, /boilerplate
• Convention cache: .claude/cache/scaffold/
  • conventions.json: Project-specific patterns
  • templates/: Cached feature templates

Cache Invalidation:

• Session cache: Cleared on completion or explicit new command
• Framework cache: Valid until project structure changes
• Convention cache: Valid for 7 days or until pattern mismatch

Shared Caches:

• /understand: Framework and structure analysis
• /implement: Project patterns and dependencies
• /boilerplate: Framework-specific templates
• /types-generate: Type generation patterns

Usage Examples

Optimized Flow (1,200-2,000 tokens):

# First scaffolding in project
claude "scaffold UserProfile"

Step 1: Check session (50 tokens)
Step 2: Load framework cache (100 tokens, cache hit)
Step 3: Find template features (150 tokens, Glob)
Step 4: Read one template (500 tokens)
Step 5: Generate plan (200 tokens)
Step 6: Create files with heredocs (600 tokens)
Total: 1,600 tokens

Resume Flow (300-600 tokens):

# Continue scaffolding
claude "scaffold resume"

Step 1: Read state.json (100 tokens)
Step 2: Load cached conventions (50 tokens)
Step 3: Generate remaining files (400 tokens)
Total: 550 tokens (85% savings)

Specific Type Flow (800-1,500 tokens):

# Scaffold specific component type
claude "scaffold --api-route users"

Step 1: Check session (50 tokens)
Step 2: Load route template (200 tokens)
Step 3: Generate route files (500 tokens)
Total: 750 tokens (75% savings)

Implementation Notes

Critical Optimizations:

1. Always check for session first - Saves 80% on resume
2. Use framework cache - Shared with /understand skill
3. Template-based generation - Avoid analysis overhead
4. Bash heredocs - Efficient multi-file creation
5. Incremental state tracking - Perfect resume support

Anti-Patterns to Avoid:

• ❌ Reading all existing features for pattern analysis
• ❌ Analyzing framework from scratch (use cache)
• ❌ Creating files one Write call at a time
• ❌ Regenerating already-created files on resume
• ❌ Full project scan without focusing on feature area

Quality Assurance:

• All files follow project conventions (from cache)
• Tests generated using project test patterns
• Imports use project import style (absolute vs relative)
• File names match project naming convention
• No duplicate scaffolding (git diff check)

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Session Intelligence

I'll maintain scaffolding progress across sessions:

Session Files (in current project directory):

• scaffold/plan.md - Scaffolding plan and component list
• scaffold/state.json - Created files and progress

IMPORTANT: Session files are stored in a scaffold folder in your current project root

Auto-Detection:

• If session exists: Resume incomplete scaffolding
• If no session: Create new scaffolding plan
• Commands: resume, status, new

Phase 1: Pattern Discovery

MANDATORY FIRST STEPS:

1. Check if scaffold directory exists in current working directory
2. If directory exists, check for session files:
   • Look for scaffold/state.json
   • Look for scaffold/plan.md
   • If found, resume from existing session
3. If no directory or session exists:
   • Analyze project patterns
   • Create scaffolding plan
   • Initialize progress tracking
4. Show scaffolding preview before creating

Note: Always look for session files in the current project's scaffold/ folder, not ../../../scaffold/ or absolute paths

I'll discover your project patterns:

Pattern Analysis:

• File organization structure
• Naming conventions
• Testing patterns
• Import/export styles
• Documentation standards

Smart Detection:

• Find similar features already implemented
• Identify architectural patterns
• Detect testing frameworks
• Understand build configuration

Phase 2: Scaffolding Planning

Based on patterns, I'll create a scaffolding plan:

Component Structure:

• Main feature files
• Test files
• Documentation
• Configuration updates
• Integration points

I'll write this plan to scaffold/plan.md with:

• Each file to create
• Template patterns to follow
• Integration requirements
• Creation order

Phase 3: Intelligent Generation

I'll generate files matching your patterns:

Pattern Matching:

• Use your file naming style
• Follow your directory structure
• Match your code conventions
• Apply your testing patterns

Content Generation:

• Boilerplate from existing code
• Imports matching your style
• Test structure from your patterns
• Documentation in your format

Phase 4: Incremental Creation

I'll create files systematically:

Execution Process:

1. Create directory structure
2. Generate each component file
3. Add appropriate tests
4. Update integration points
5. Track each creation in state

Progress Tracking:

• Mark each file created in plan
• Update state with file paths
• Create meaningful commits

Phase 5: Integration

After scaffolding:

• Update route configurations
• Add to module exports
• Update build configuration
• Verify everything connects

Context Continuity

Session Resume: When you return and run /scaffold or /scaffold resume:

• Load existing plan and progress
• Show what was already created
• Continue from last component
• Maintain pattern consistency

Progress Example:

RESUMING SCAFFOLDING
├── Feature: UserDashboard
├── Created: 5 of 8 files
├── Last: components/UserStats.tsx
└── Next: tests/UserStats.test.tsx

Continuing scaffolding...

Practical Examples

Start Scaffolding:

/scaffold UserProfile          # Create user profile feature
/scaffold "auth module"        # Create authentication module
/scaffold PaymentService       # Create payment service

Session Control:

/scaffold resume    # Continue existing scaffolding
/scaffold status    # Check what's been created
/scaffold new       # Start fresh scaffolding

Safety Guarantees

Protection Measures:

• Preview before creation
• Incremental file generation
• Pattern validation
• Integration verification

Important: I will NEVER:

• Overwrite existing files
• Break existing imports
• Add AI attribution
• Create without following patterns

What I'll Actually Do

1. Analyze deeply - Understand your patterns
2. Plan completely - Map all components
3. Generate intelligently - Match your style
4. Track precisely - Perfect continuity
5. Integrate seamlessly - Connect everything

I'll maintain complete continuity between sessions, always resuming exactly where we left off with consistent pattern application.