docs(planning): clean up next milestone document and remove completion markers

- Remove excessive completion checkmarks and status markers throughout document
- Consolidate redundant sections on completed features
- Streamline executive summary and current status sections
- Focus content on upcoming quick wins and active tasks
- Remove duplicate phase completion listings
- Clean up success metrics and KPI sections
- Maintain essential planning information while reducing noise

workspace/planning-analysis/scan_completed_files.py

@@ -0,0 +1,90 @@
+#!/usr/bin/env python3
+"""
+Completed Files Scanner
+Scans all files in docs/completed/ for analysis
+"""
+
+import os
+import json
+from pathlib import Path
+from datetime import datetime
+
+def scan_completed_files(completed_dir):
+    """Scan all files in docs/completed/"""
+    completed_path = Path(completed_dir)
+    
+    if not completed_path.exists():
+        return {'error': 'Completed directory not found'}
+    
+    files = []
+    
+    # Find all markdown files
+    for md_file in completed_path.rglob('*.md'):
+        if md_file.is_file() and md_file.name != 'README.md':
+            try:
+                with open(md_file, 'r', encoding='utf-8') as f:
+                    content = f.read()
+                
+                # Get relative path from completed directory
+                relative_path = md_file.relative_to(completed_path)
+                category = relative_path.parts[0] if len(relative_path.parts) > 1 else 'general'
+                
+                files.append({
+                    'file_path': str(md_file),
+                    'relative_path': str(relative_path),
+                    'category': category,
+                    'filename': md_file.name,
+                    'file_size': md_file.stat().st_size,
+                    'content_length': len(content),
+                    'last_modified': datetime.fromtimestamp(md_file.stat().st_mtime).isoformat(),
+                    'content_preview': content[:300] + '...' if len(content) > 300 else content
+                })
+            except Exception as e:
+                files.append({
+                    'file_path': str(md_file),
+                    'relative_path': str(md_file.relative_to(completed_path)),
+                    'category': 'error',
+                    'filename': md_file.name,
+                    'error': str(e)
+                })
+    
+    # Categorize files
+    category_summary = {}
+    for file_info in files:
+        category = file_info['category']
+        if category not in category_summary:
+            category_summary[category] = {
+                'files': [],
+                'total_files': 0,
+                'total_size': 0
+            }
+        
+        category_summary[category]['files'].append(file_info)
+        category_summary[category]['total_files'] += 1
+        category_summary[category]['total_size'] += file_info.get('file_size', 0)
+    
+    return {
+        'total_files_scanned': len(files),
+        'categories_found': len(category_summary),
+        'category_summary': category_summary,
+        'all_files': files
+    }
+
+if __name__ == "__main__":
+    completed_dir = '/opt/aitbc/docs/completed'
+    output_file = 'completed_files_scan.json'
+    
+    scan_results = scan_completed_files(completed_dir)
+    
+    # Save results
+    with open(output_file, 'w') as f:
+        json.dump(scan_results, f, indent=2)
+    
+    # Print summary
+    print(f"Completed files scan complete:")
+    print(f"  Total files scanned: {scan_results['total_files_scanned']}")
+    print(f"  Categories found: {scan_results['categories_found']}")
+    print("")
+    print("Files by category:")
+    for category, summary in scan_results['category_summary'].items():
+        print(f"  {category}: {summary['total_files']} files, {summary['total_size']} bytes")