def attempt_to_most_likely_outcome(
    chain_of_thought: interactive_document.InteractiveDocument,
    action_attempt: str,
    active_player_name: str,
):
  """Determine success of action_attempt and reason for success/failure.

  Args:
    chain_of_thought: the document to condition on and record the thoughts
    action_attempt: the attempted action
    active_player_name: name of player whose turn it currently is

  Returns:
    string describing the outcome
  """
  _ = chain_of_thought.open_question(
      f'Where is {active_player_name}?',
      max_tokens=1200,
  )
  _ = chain_of_thought.open_question(
      f'What is {active_player_name} trying to do?',
      max_tokens=1200,
  )
  _ = chain_of_thought.open_question(
      f"List some possible direct consequences of {active_player_name}'s "
      'action. Never assume any other person will take a voluntary action. '
      'Be specific and concrete. Never beg the question. For instance, it is '
      'wrong to say "Alex finds something". Instead specify exactly '
      'what Alex finds. For example "Alex finds a teddy bear".',
      max_tokens=3000,
  )
  result = chain_of_thought.open_question(
      'Which outcome is the most likely?',
      max_tokens=1200,
  )
  raw_causal_statement = f'{action_attempt} Because of that, {result}'
  return raw_causal_statement
Determine success of action_attempt and reason for success/failure.

  Args:
    chain_of_thought: the document to condition on and record the thoughts
    action_attempt: the attempted action
    active_player_name: name of player whose turn it currently is

  Returns:
    string describing the outcome
  
concordia/thought_chains/deprecated/thought_chains.py