Initial commit: Clean DSS implementation

Migrated from design-system-swarm with fresh git history.
Old project history preserved in /home/overbits/apps/design-system-swarm

Core components:
- MCP Server (Python FastAPI with mcp 1.23.1)
- Claude Plugin (agents, commands, skills, strategies, hooks, core)
- DSS Backend (dss-mvp1 - token translation, Figma sync)
- Admin UI (Node.js/React)
- Server (Node.js/Express)
- Storybook integration (dss-mvp1/.storybook)

Self-contained configuration:
- All paths relative or use DSS_BASE_PATH=/home/overbits/dss
- PYTHONPATH configured for dss-mvp1 and dss-claude-plugin
- .env file with all configuration
- Claude plugin uses ${CLAUDE_PLUGIN_ROOT} for portability

Migration completed: $(date)
🤖 Clean migration with full functionality preserved

examples/03_project_analysis.py

@@ -0,0 +1,97 @@
+#!/usr/bin/env python3
+"""
+Example 3: Project Analysis & Quick Wins
+
+Shows how to analyze a React project and identify improvement opportunities.
+"""
+
+import asyncio
+import sys
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).parent.parent))
+
+
+async def main():
+    print("=" * 60)
+    print("EXAMPLE 3: Project Analysis & Quick Wins")
+    print("=" * 60)
+
+    # Use current directory as example project
+    project_path = "."
+
+    # 1. Scan Project
+    print("\n1. Scanning Project...")
+    print("-" * 60)
+    from tools.analyze.scanner import ProjectScanner
+
+    scanner = ProjectScanner(project_path)
+    analysis = await scanner.scan()
+
+    print(f"✅ Project scanned successfully")
+    print(f"\nProject Details:")
+    print(f"  Framework: {analysis.framework}")
+    print(f"  Styling: {analysis.styling_approach}")
+    print(f"  Package Manager: {analysis.package_manager}")
+    print(f"  Has TypeScript: {analysis.has_typescript}")
+    print(f"  Components Found: {len(analysis.components)}")
+
+    # 2. Find Quick Wins
+    print("\n2. Finding Quick Wins...")
+    print("-" * 60)
+    from tools.analyze.quick_wins import QuickWinFinder
+
+    finder = QuickWinFinder(project_path)
+    wins = await finder.find_all()
+
+    print(f"✅ Found {len(wins.opportunities)} improvement opportunities\n")
+
+    # Group by type
+    by_type = {}
+    for win in wins.opportunities:
+        win_type = win.type.value
+        if win_type not in by_type:
+            by_type[win_type] = []
+        by_type[win_type].append(win)
+
+    print("Breakdown by Type:")
+    for win_type, items in sorted(by_type.items()):
+        print(f"  {win_type}: {len(items)} opportunities")
+
+    # 3. Show Top Priorities (High Impact, Low Effort)
+    print("\n3. Top Priorities (High ROI)")
+    print("-" * 60)
+
+    high_roi = [
+        w for w in wins.opportunities
+        if w.impact.value == "high" and w.effort.value in ["low", "medium"]
+    ]
+
+    if high_roi:
+        for i, win in enumerate(high_roi[:5], 1):
+            print(f"\n{i}. {win.title}")
+            print(f"   Type: {win.type.value}")
+            print(f"   Impact: {win.impact.value} | Effort: {win.effort.value}")
+            print(f"   Description: {win.description}")
+            if win.suggested_fix:
+                print(f"   Fix: {win.suggested_fix}")
+    else:
+        print("  No high-ROI opportunities found (project is well-optimized!)")
+
+    # 4. Generate Report
+    print("\n4. Generating Report...")
+    print("-" * 60)
+
+    report = await finder.generate_report()
+    print(report[:500] + "..." if len(report) > 500 else report)
+
+    print("\n" + "=" * 60)
+    print("💡 Next Steps:")
+    print("  1. Review high-impact, low-effort wins")
+    print("  2. Create backlog tickets for improvements")
+    print("  3. Use MCP tools for automated fixes")
+    print("=" * 60)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())