Return code: 0
Duration: 140.7s

=== 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("Task 1-2: Problem analysis and predicate de...
  python_exec: import random
  python_exec: defining function generate_asp_facts()
  python_exec: asp_rules = """
  python_exec: defining function on_model()
  python_exec: if solution_data:
  save_code: {'code': 'import clingo\nimpor...
  report_issue: {'text': 'All is fine - no iss...


                                    Summary                                     

I've successfully completed the tournament ranking task using Answer Set        
Programming (ASP) with the clingo Python API.                                   

Solution Overview:                                                              

 • Approach: Modeled the problem as a constraint satisfaction problem in ASP    
 • Result: Found a valid ranking with 598 weighted violations (within the 650   
   bound)                                                                       
 • Verification: All 7 constraint types are satisfied:                          
    1 ✓ Must-above constraints (20 pairs)                                       
    2 ✓ Adjacency bans (15 pairs)                                               
    3 ✓ Forbid-top constraints (8 teams)                                        
    4 ✓ Forbid-block constraints (5 teams)                                      
    5 ✓ Diversity constraint (max 2 per group in any 5-team window)             
    6 ✓ Seed quota (6 seeds in top 10)                                          
    7 ✓ Violation bound (598 ≤ 650)                                             

Key Implementation Details:                                                     

 • Generated 435 match results from the specified random seed pattern           
 • Used choice rules to create a bijective mapping between teams and positions  
 • Encoded all constraints as integrity constraints (:- ...)                    
 • Calculated violations and enforced the bound using aggregates                
 • Extracted and formatted the solution as required JSON                        

The solution executes efficiently and produces a valid ranking that satisfies   
all requirements.                                                               

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

🔧 Tool Usage:
  python_exec            6 calls
  report_issue           1 calls
  save_code              1 calls

💬 Token Consumption:
  Input tokens:        148,535
  Output tokens:       6,883
  Total tokens:        155,418

⏱️  Execution time: 2m 19.4s
==================================================


=== STDERR ===
