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用于信托领域项目尽调中的融资主体尽调助手-地产版场景。支持结构化输入处理、规则分析与Markdown结果输出。
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Read SKILL.md and any companion files shown by SkillsMP before deciding whether to install.
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npx skills add https://github.com/aifinlab/FinClaw --skill financing-entity-dd-real-estateThe command stays on one line. Scroll horizontally to inspect it before copying.
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Showing SKILL.md
| name | financing-entity-dd-real-estate |
| description | 用于信托领域项目尽调中的融资主体尽调助手-地产版场景。支持结构化输入处理、规则分析与Markdown结果输出。 |
本技能面向“项目尽调 / 主体尽调”业务单元，输出结构化分析报告与风险提示，支持尽调、法务、风控及存续管理流程中的基础判断。
id, name, text, status, timestamp 及相关业务字段按顺序执行：
node scripts/t772_preprocess.js --input input.jsonl --output processed.json
python scripts/t772_analysis.py --input processed.json --rules config/rules.json --baseline reference/baseline.json --output report.md
# 调用 skill
result = run_skill({
"param1": "value1",
"param2": "value2"
})
python scripts/run_skill.py --input data.json
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