<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def get_siblings_content(self, current_sibling, baselinescore_siblings_para):
 """\ adds any siblings that may have a decent score to this node """

        if current_sibling.tag == 'p' and len(self.parser.getText(current_sibling)) > 0:
            e0 = current_sibling
            if e0.tail:
                e0 = deepcopy(e0)
                e0.tail = ''
            return [e0]
        else:
            potential_paragraphs = self.parser.getElementsByTag(current_sibling, tag='p')
            if potential_paragraphs is None:
                return None
            else:
                ps = []
                for first_paragraph in potential_paragraphs:
                    text = self.parser.getText(first_paragraph)
                    if len(text) > 0:
                        word_stats = self.stopwords_class(language=self.language).get_stopword_count(text)
                        paragraph_score = word_stats.get_stopword_count()
                        sibling_baseline_score = float(.30)
                        high_link_density = self.is_highlink_density(first_paragraph)
                        score = float(baselinescore_siblings_para * sibling_baseline_score)
                        if score < paragraph_score and not high_link_density:
                            p = self.parser.createElement(tag='p', text=text, tail=None)
                            ps.append(p)
                return ps