Return code: 0
Duration: 62.2s

=== STDOUT ===
🚀 Running coder
📦 Dynamic packages: clingo
🤖 Creating agent with model: anthropic/claude-sonnet-4.5
🤖 Using model: anthropic/claude-sonnet-4.5
  python_exec: print("Starting ASP model design for 9-Queens Domi...
  python_exec: defining function solve_queen_domination()
  python_exec: defining function verify_solution()
  save_code: {'code': 'import clingo\nimpor...
  report_issue: {'text': 'All is fine - no iss...


                                    Summary                                     

I've successfully completed the 9-Queens Domination Problem using Answer Set    
Programming with clingo.                                                        

Solution Details:                                                               

 • Optimal number of queens: 5 (as expected)                                    
 • Example placement: [[1, 6], [3, 1], [5, 7], [6, 3], [8, 8]]                  
 • All 81 squares dominated: ✓ Verified                                         

ASP Model Structure:                                                            

 1 Facts: Defined 9×9 board (rows and columns 0-8)                              
 2 Choice rule: Allowed flexible queen placement                                
 3 Domination rules: A square is dominated if a queen is:                       
    • On that square                                                            
    • In the same row                                                           
    • In the same column                                                        
    • On the same diagonal (R-C constant)                                       
    • On the same anti-diagonal (R+C constant)                                  
 4 Constraint: All squares must be dominated                                    
 5 Optimization: Minimize the number of queens                                  

The solution has been saved and outputs the required JSON format.               

==================================================
📊 Execution Statistics
==================================================

🔧 Tool Usage:
  python_exec            3 calls
  report_issue           1 calls
  save_code              1 calls

💬 Token Consumption:
  Input tokens:        58,940
  Output tokens:       2,794
  Total tokens:        61,734

⏱️  Execution time: 1m 0.9s
==================================================


=== STDERR ===
