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A股逆向选择/信息不对称分析。当用户说"逆向选择"、"adverse selection"、"信息不对称"、"知情交易者"、"逆向选择成本"、"信息劣势"时触发。基于 cn-stock-data 获取数据，度量逆向选择与信息不对称程度。支持 formal/brief 两种输出风格。
A股量价异常检测/异动监控。当用户说"异常检测"、"异动"、"anomaly"、"量价异常"、"异常波动"、"XX有异动"时触发。量化检测股价和成交量异常。支持formal和brief风格。
A股自相关/序列相关性/收益率自相关结构分析。当用户说"自相关"、"autocorrelation"、"序列相关"、"收益率预测性"、"动量还是反转"、"自相关系数"、"ACF"、"PACF"、"Ljung-Box"、"收益率是否可预测"、"随机游走检验"时触发。MUST USE when user asks about return autocorrelation, serial correlation tests, or whether a stock's returns are predictable. 量化分析收益率的自相关结构（ACF/PACF、Ljung-Box检验、随机游走检验）。支持formal和brief风格。
Based on SOC occupation classification
Showing SKILL.md
| name | contract-clause-assistant |
| description | 用于合同条款结构化识别与完整性检查，自动识别关键条款类型并提示缺失项。适用于信托业务合同起草、条款体检、法务预审场景。 |
本技能用于对合同条款进行基础解析与完整性检查，重点覆盖：
支持 JSON 数组或 JSONL，每条记录建议包含：
contract_nameclause_noclause_titleclause_text使用 scripts/contract_clause_analysis.py 生成报告：
python scripts/contract_clause_analysis.py \
--input clauses.json \
--output clause_report.md
可选参数：
--required：自定义关键条款清单 JSON