Return code: 0
Duration: 174.9s

=== STDOUT ===
🚀 Running coder
📦 Dynamic packages: clingo
🤖 Creating agent with model: anthropic/claude-sonnet-4.5
🤖 Using model: anthropic/claude-sonnet-4.5
  python_exec: import random
  python_exec: defining function generate_asp_program()
  python_exec: rules = """
  python_exec: defining function on_model()
  python_exec: defining function verify_solution()
  python_exec: defining function on_model()
  python_exec: output = {
  save_code: {'code': 'import clingo\nimpor...
  python_exec: executing file 011_tournament_ranking_hard_task_code.py
  report_issue: {'text': 'All is fine - no iss...

Perfect! I have successfully completed the task. The solution:                  


                                    Summary                                     

I created an ASP-based solution using the clingo Python API that finds a valid  
ranking for 30 teams in a weighted round-robin tournament with 7 complex        
constraint types.                                                               

Solution Found:                                                                 

 • Ranking: T23, T24, T03, T09, T02, T25, T07, T14, T10, T04, T21, T01, T11,    
   T27, T12, T26, T06, T17, T13, T05, T29, T18, T20, T22, T28, T08, T19, T30,   
   T15, T16                                                                     
 • Violations: 615 (within the 650 bound)                                       
 • Valid: All constraints satisfied                                             
 • Total Absolute Deviation: 242                                                

All 7 Constraints Satisfied:                                                    

 1 ✓ Must-above (20 pairs)                                                      
 2 ✓ Adjacency bans (15 pairs)                                                  
 3 ✓ Forbid-top (8 teams)                                                       
 4 ✓ Forbid-block (5 teams)                                                     
 5 ✓ Diversity (max 2 from same group in any 5-team window)                     
 6 ✓ Seed quota (6 seeds in top 10)                                             
 7 ✓ Violation bound (615 ≤ 650)                                                

The solution uses ASP choice rules to generate candidate rankings and integrity 
constraints to enforce all requirements, finding a satisfying solution          
efficiently.                                                                    

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

🔧 Tool Usage:
  python_exec            8 calls
  report_issue           1 calls
  save_code              1 calls

💬 Token Consumption:
  Input tokens:        185,626
  Output tokens:       8,897
  Total tokens:        194,523

⏱️  Execution time: 2m 51.4s
==================================================


=== STDERR ===
