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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。
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Showing SKILL.md
| name | semi-structured-data-ingestion |
| description | 用于Excel/表单接入的半结构化数据接入原子 skill，适用于通用行业数据接入场景。 |
本 Skill 支持多种半结构化数据源输入格式，核心数据来源包括：
说明：本 Skill 不包含数据采集功能，需要用户提供半结构化数据文件。建议数据格式规范，以便进行准确的数据接入。
本 Skill 提供全面的半结构化数据接入能力，涵盖多种接入功能：
{
"source_info": {
"source_type": "excel_file",
"source_file": "financial_data.xlsx",
"file_size": 2048000,
"sheet_count": 3
},
"ingestion_config": {
"sheets": ["利润表", "资产负债表", "现金流量表"],
"header_row": 1,
"data_start_row": 2,
"encoding": "UTF-8"
},
"ingestion_results": {
"total_sheets": 3,
"total_records": 5000,