276ed71f31
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
98 lines
2.8 KiB
Python
Executable File
98 lines
2.8 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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Example 3: Project Analysis & Quick Wins
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Shows how to analyze a React project and identify improvement opportunities.
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"""
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import asyncio
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import sys
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).parent.parent))
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async def main():
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print("=" * 60)
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print("EXAMPLE 3: Project Analysis & Quick Wins")
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print("=" * 60)
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# Use current directory as example project
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project_path = "."
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# 1. Scan Project
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print("\n1. Scanning Project...")
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print("-" * 60)
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from tools.analyze.scanner import ProjectScanner
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scanner = ProjectScanner(project_path)
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analysis = await scanner.scan()
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print(f"✅ Project scanned successfully")
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print(f"\nProject Details:")
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print(f" Framework: {analysis.framework}")
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print(f" Styling: {analysis.styling_approach}")
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print(f" Package Manager: {analysis.package_manager}")
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print(f" Has TypeScript: {analysis.has_typescript}")
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print(f" Components Found: {len(analysis.components)}")
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# 2. Find Quick Wins
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print("\n2. Finding Quick Wins...")
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print("-" * 60)
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from tools.analyze.quick_wins import QuickWinFinder
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finder = QuickWinFinder(project_path)
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wins = await finder.find_all()
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print(f"✅ Found {len(wins.opportunities)} improvement opportunities\n")
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# Group by type
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by_type = {}
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for win in wins.opportunities:
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win_type = win.type.value
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if win_type not in by_type:
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by_type[win_type] = []
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by_type[win_type].append(win)
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print("Breakdown by Type:")
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for win_type, items in sorted(by_type.items()):
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print(f" {win_type}: {len(items)} opportunities")
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# 3. Show Top Priorities (High Impact, Low Effort)
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print("\n3. Top Priorities (High ROI)")
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print("-" * 60)
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high_roi = [
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w for w in wins.opportunities
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if w.impact.value == "high" and w.effort.value in ["low", "medium"]
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]
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if high_roi:
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for i, win in enumerate(high_roi[:5], 1):
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print(f"\n{i}. {win.title}")
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print(f" Type: {win.type.value}")
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print(f" Impact: {win.impact.value} | Effort: {win.effort.value}")
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print(f" Description: {win.description}")
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if win.suggested_fix:
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print(f" Fix: {win.suggested_fix}")
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else:
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print(" No high-ROI opportunities found (project is well-optimized!)")
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# 4. Generate Report
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print("\n4. Generating Report...")
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print("-" * 60)
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report = await finder.generate_report()
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print(report[:500] + "..." if len(report) > 500 else report)
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print("\n" + "=" * 60)
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print("💡 Next Steps:")
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print(" 1. Review high-impact, low-effort wins")
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print(" 2. Create backlog tickets for improvements")
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print(" 3. Use MCP tools for automated fixes")
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print("=" * 60)
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if __name__ == "__main__":
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asyncio.run(main())
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