input: from typing import List
  
  def extract_verbs(sentence: str) -> List[str]:
      """This function uses the Natural Language Toolkit (NLTK) to extract verbs from a given sentence.
      The input sentence is first tokenized and then part-of-speech tagged. The function then filters
      the tokens to include only those that are verbs. The function returns a list of verbs.
      
      >>> extract_verbs("The cat jumped over the moon.")
      ['jumped']
      >>> extract_verbs("She walked quickly to the store.")
      ['walked', 'quickly']
      """
      tokens = nltk.word_tokenize(sentence)
      tags = nltk.pos_tag(tokens)
      verbs = [word for word, pos in tags if pos.startswith('V')]
      return verbs
output:     import nltk
      nltk.download('punkt')
      nltk.download('averaged_perceptron_tagger')