Return code: 0
Duration: 67.1s

=== 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("Planning complete. Starting implementation....
  python_exec: import clingo
  python_exec: defining function on_model()
  python_exec: if result.satisfiable and solution:
  python_exec: queens_positions = solution["queens"]
  save_code: {'code': 'import clingo\nimpor...
  report_issue: {'text': 'All is fine - no iss...


                                    Summary                                     

I've successfully completed the queen domination problem using Answer Set       
Programming (ASP) with clingo. Here's what was accomplished:                    

                               Solution Overview                                

 • Optimal number of queens: 5 (matches expected value)                         
 • Queen positions: [0,2], [2,6], [4,0], [6,4], [8,8]                           
 • Coverage: All 81 squares on the 9×9 board are dominated                      

                                ASP Model Design                                

The solution uses:                                                              

 1 Facts: Define the 9×9 board with rows and columns 0-8                        
 2 Choice rule: Allow queens to be placed anywhere on the board                 
 3 Domination rules: A square is dominated if a queen exists on:                
    • The same row                                                              
    • The same column                                                           
    • The same diagonal (positive slope: R-C constant)                          
    • The same diagonal (negative slope: R+C constant)                          
 4 Constraint: Every square must be dominated                                   
 5 Optimization: Minimize the number of queens using #minimize                  

The solution was verified to ensure all 81 squares are properly dominated by the
5 queens, and the code executes efficiently within the time constraints.        

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

🔧 Tool Usage:
  python_exec            5 calls
  report_issue           1 calls
  save_code              1 calls

💬 Token Consumption:
  Input tokens:        109,968
  Output tokens:       2,581
  Total tokens:        112,549

⏱️  Execution time: 1m 6.0s
==================================================


=== STDERR ===
