feat: add 33 skills from vudovn/antigravity-kit

- Added: api-patterns, app-builder, architecture, bash-linux, behavioral-modes,
  clean-code, code-review-checklist, database-design, deployment-procedures,
  docker-expert, documentation-templates, game-development, geo-fundamentals,
  i18n-localization, lint-and-validate, mobile-design, nestjs-expert,
  nextjs-best-practices, nodejs-best-practices, parallel-agents,
  performance-profiling, plan-writing, powershell-windows, prisma-expert,
  python-patterns, react-patterns, red-team-tactics, seo-fundamentals,
  server-management, tailwind-patterns, tdd-workflow, typescript-expert,
  vulnerability-scanner
- Updated README: skill count 179 → 223
- Added credit for vudovn/antigravity-kit (MIT License)

Source: https://github.com/vudovn/antigravity-kit

skills/performance-profiling/scripts/lighthouse_audit.py

@@ -0,0 +1,76 @@
+#!/usr/bin/env python3
+"""
+Skill: performance-profiling
+Script: lighthouse_audit.py
+Purpose: Run Lighthouse performance audit on a URL
+Usage: python lighthouse_audit.py https://example.com
+Output: JSON with performance scores
+Note: Requires lighthouse CLI (npm install -g lighthouse)
+"""
+import subprocess
+import json
+import sys
+import os
+import tempfile
+
+def run_lighthouse(url: str) -> dict:
+    """Run Lighthouse audit on URL."""
+    try:
+        with tempfile.NamedTemporaryFile(suffix='.json', delete=False) as f:
+            output_path = f.name
+        
+        result = subprocess.run(
+            [
+                "lighthouse",
+                url,
+                "--output=json",
+                f"--output-path={output_path}",
+                "--chrome-flags=--headless",
+                "--only-categories=performance,accessibility,best-practices,seo"
+            ],
+            capture_output=True,
+            text=True,
+            timeout=120
+        )
+        
+        if os.path.exists(output_path):
+            with open(output_path, 'r') as f:
+                report = json.load(f)
+            os.unlink(output_path)
+            
+            categories = report.get("categories", {})
+            return {
+                "url": url,
+                "scores": {
+                    "performance": int(categories.get("performance", {}).get("score", 0) * 100),
+                    "accessibility": int(categories.get("accessibility", {}).get("score", 0) * 100),
+                    "best_practices": int(categories.get("best-practices", {}).get("score", 0) * 100),
+                    "seo": int(categories.get("seo", {}).get("score", 0) * 100)
+                },
+                "summary": get_summary(categories)
+            }
+        else:
+            return {"error": "Lighthouse failed to generate report", "stderr": result.stderr[:500]}
+            
+    except subprocess.TimeoutExpired:
+        return {"error": "Lighthouse audit timed out"}
+    except FileNotFoundError:
+        return {"error": "Lighthouse CLI not found. Install with: npm install -g lighthouse"}
+
+def get_summary(categories: dict) -> str:
+    """Generate summary based on scores."""
+    perf = categories.get("performance", {}).get("score", 0) * 100
+    if perf >= 90:
+        return "[OK] Excellent performance"
+    elif perf >= 50:
+        return "[!] Needs improvement"
+    else:
+        return "[X] Poor performance"
+
+if __name__ == "__main__":
+    if len(sys.argv) < 2:
+        print(json.dumps({"error": "Usage: python lighthouse_audit.py <url>"}))
+        sys.exit(1)
+    
+    result = run_lighthouse(sys.argv[1])
+    print(json.dumps(result, indent=2))