从括号DSL字符串中提取业务实体 — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited 从括号DSL字符串中提取业务实体 (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
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。
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.