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yzy1

自动识别量表维度（前缀+数字命名），计算各维度均分，支持反向计分和缺失处理。输入支持 Excel (.xlsx) 和 CSV

Y-EGG

@y-egg

What This Skill Does

Automatically identifies questionnaire dimensions from column names (prefix + trailing number), calculates dimension means, supports reverse scoring and missing value handling. Accepts Excel (.xlsx) and CSV input files.

Replaces manual scoring in spreadsheet software by automating dimension recognition, reverse coding, and mean calculation for psychological scales.

When to Use It

  • Score a psychology questionnaire with multiple subscales from an Excel file
  • Apply reverse scoring to specific items in a survey dataset
  • Calculate dimension means while handling missing responses (up to 50% per dimension)
  • Batch-process multiple scale datasets with consistent column naming conventions
  • Generate scored output files appended with dimension mean columns

Install

$ openclaw skills install @y-egg/scale-scorer

量表维度均分自动计算工具

功能说明

针对心理学问卷/量表原始数据，自动执行以下操作：

  1. 智能识别维度：根据列名规则（维度前缀 + 末尾数字，如 T1RZTD1、T1RZTD2）自动将题目分组为不同维度（至少包含 2 题）
  2. 反向计分处理：支持通过配置文件指定需反向计分的题目，自动转换为正值（默认量表范围 1–5，可自定义）
  3. 维度均分计算：对每个维度内的题目计算平均值，缺失值≤50%时用剩余题目均值替代，超阈则标记为缺失
  4. 输出结构化结果：在原始数据右侧追加每个维度的均分列（列名为维度前缀，如 T1RZTD），不影响原有数据

支持输入格式：Excel（.xlsx）和 CSV（.csv），输出格式与输入一致，自动生成 _scored 文件。

使用方式

命令行调用（基础用法）

python scale-scorer.py "数据文件路径"

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