菜单
Convert Pingouin results into compact, polished APA-style or Chinese psychology result sections with tables, assumption notes, and uncertainty caveats.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Screen psychology datasets before Pingouin analysis: variable types, missingness, duplicates, long/wide shape, assumption checks, and safer preprocessing.
Run or generate Pingouin code for multivariate comparisons — Hotelling's T-squared test (multivariate_ttest) — plus the multivariate assumption checks box_m (equal covariance) and multivariate_normality, for designs with several dependent variables.
Route psychology statistics requests to the smallest Pingouin workflow. Use when the user asks what analysis to run, gives a psychology design, asks to analyze data with Pingouin, or needs lower-token guidance before code generation.
Compute or generate Pingouin Bayes factors for t tests, correlations, and proportions (bayesfactor_ttest, bayesfactor_pearson, bayesfactor_binom), and read the BF10 already returned by pg.ttest and pg.corr.
Run or generate Pingouin code for categorical / contingency-table analyses — chi-square test of independence, McNemar's paired test, 2x2 crosstabs, and chi-square power — for psychology data with nominal variables.
Run or generate Pingouin code for rank-based non-parametric tests — Mann-Whitney U, Wilcoxon signed-rank, Kruskal-Wallis, Friedman, and Cochran Q — when outcomes are ordinal or parametric assumptions fail.
| name | pg-reporting |
| description | Convert Pingouin results into compact, polished APA-style or Chinese psychology result sections with tables, assumption notes, and uncertainty caveats. |
Use after a Pingouin result table exists or when the user asks to beautify/statistically polish output.
Read:
../../references/supervision-gates.md../../references/apa-output-template.md../../references/pingouin-api-quickref.mdNeed one of:
If no numeric results are available, generate a fill-in template and refuse to invent numbers.
For Chinese users, default to Chinese prose with English statistical symbols:
**结果。** 独立样本 t 检验显示，A 组得分显著高于 B 组，*t*(38) = 2.41, p = .021, Cohen's d = 0.76, 95% CI [0.12, 1.38]。
For English:
An independent-samples t test showed that Group A scored higher than Group B, *t*(38) = 2.41, *p* = .021, Cohen's d = 0.76, 95% CI [0.12, 1.38].
p < .001.