Return code: 0
Duration: 145.0s

=== 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 clingo
  python_exec: defining function analyze_current_election()
  python_exec: defining function find_condorcet_winner()
  python_exec: defining function check_coalition_manipulation()
  python_exec: print("Testing coalition size 2...")
  python_exec: defining function find_all_strategic_opportunities()
  python_exec: defining function get_preference_list()
  save_code: {'code': 'import clingo\nimpor...
  python_exec: executing file 059_strategic_voting_easy_task_code.py
  report_issue: {'text': 'All is fine - no iss...


                                    Summary                                     

I've successfully completed the strategic voting analysis task using Answer Set 
Programming (ASP) with the clingo Python API. Here's what was accomplished:     

                                  Key Results:                                  

 1 Current Election Outcome: Candidate A wins with 2 votes (B: 1, C: 1)         
 2 Condorcet Winner: None exists - all pairwise comparisons result in 2-2 ties, 
   creating a voting cycle                                                      
 3 Minimum Coalition Size: 2 voters (matching the expected optimal value)       
    • Coalition size 1 cannot manipulate the election                           
    • Coalition size 2 can successfully change the outcome                      
 4 Strategic Opportunities Detected:                                            
    • V3 can cooperate with V1 to elect B or C (both preferred over A)          
    • V4 can cooperate with V1 to elect B or C (both preferred over A)          
    • Multiple valid manipulation strategies exist                              

                              ASP Model Features:                               

 • Choice rules to select coalition members with exact cardinality constraints  
 • Vote counting using aggregates (#count, #max)                                
 • Winner determination based on plurality voting                               
 • Benefit detection ensuring coalition members prefer new outcome              
 • Constraints preventing trivial solutions (must change winner, must benefit   
   someone)                                                                     

The solution correctly identifies that this election is not manipulation-proof  
and that strategic voting opportunities exist with a minimum coalition of 2     
voters.                                                                         

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

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

💬 Token Consumption:
  Input tokens:        245,845
  Output tokens:       8,079
  Total tokens:        253,924

⏱️  Execution time: 2m 22.7s
==================================================


=== STDERR ===
