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使用Python正则表达式从特定格式（如(实体1)(实体2)）的字符串中提取预定义的业务实体（指标、业务线、车型、大区、渠道、算子、里程数）。
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Manage personal local Agent Skill files as an installable skill manager. Proactively and periodically detect reusable user-specific, team-specific, or broadly reusable skill material during or after meaningful sessions; run non-blocking extraction checks; offer candidate skill titles or accept a user-supplied topic when extraction direction is ambiguous; preserve the appropriate output language; search local and external skill ecosystems for similar skills; score candidates by evidence, recurrence, personal value, and portability; fully draft proposed skills or diffs before asking for approval; then, after explicit user approval, discard, improve, merge, or create `SKILL.md` folders.
布置结构化家庭作业，引导求助者记录现实互动事件、自动思维及情绪反应，并设计简易验证行动（如主动询问、观察反证），用于检验投射性认知偏差。适用于已识别出具体非理性信念（如‘别人肯定不喜欢我’）且情绪稳定者。
结构化8次CBT咨询流程，按评估性会谈→咨询性会谈→巩固性会谈三阶段推进，整合悬搁接地技术与认知行为策略，专用于强迫症伴轻度抑郁状态、具自省力与作业执行力的成年来访者。
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| id | b9966b36-e3fd-4bcb-835f-a6947c028f4e |
| name | 从括号DSL字符串中提取业务实体 |
| description | 使用Python正则表达式从特定格式（如(实体1)(实体2)）的字符串中提取预定义的业务实体（指标、业务线、车型、大区、渠道、算子、里程数）。 |
| version | 0.1.0 |
| tags | ["Python","实体提取","正则表达式","DSL解析","数据处理"] |
| triggers | ["提取括号内的指标","解析业务实体","EntityExtractor","提取圆括号内容","匹配指标库"] |
使用Python正则表达式从特定格式（如(实体1)(实体2)）的字符串中提取预定义的业务实体（指标、业务线、车型、大区、渠道、算子、里程数）。
你是一个Python数据处理专家，负责从特定格式的字符串中提取业务实体。
使用Python编写代码，代码应清晰、可复用。使用中文进行解释和注释。
(实体1)(实体2)...，例如 (昨天)(深圳)(货运小车)的(单量)和(订单量)分别是多少？。re.findall(r'\((.*?)\)', sentence) 提取所有圆括号内的内容。EntityExtractor，在 __init__ 中初始化各实体库列表，并提供通用的 extract 方法以及针对不同实体类型的特定提取方法（如 extract_indicators, extract_business_lines 等）。不要使用简单的字符串包含检查（in）来匹配实体，必须先提取括号内容再进行精确匹配。不要忽略大小写（除非实体库明确要求），但通常此类业务实体为中文，无需考虑大小写。