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auto-stat-test

Selects and performs statistical tests, returning a structured JSON report with interpretations.

12|2|Updated Apr 21, 2026
Search Tags:#data-analysis#json-report#anova#statistical-testing#mann-whitney#normality#chi-square
One-click install
npx skills add https://github.com/haomingz/kimi-skills --skill auto-stat-test
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: auto-stat-test
Source: https://github.com/haomingz/kimi-skills/tree/main/skills/auto-stat-test
Command: npx skills add https://github.com/haomingz/kimi-skills --skill auto-stat-test

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires numpy, pandas, scipy, and includes scripts (resource) components.

What problem does it solve?

Automates the tedious process of selecting the correct statistical test for a given dataset and producing an interpretable report.

Core Features & Use Cases

  • Automatic test selection for two-group and multi-group data
  • Generates p-values, effect sizes, and plain-language interpretations
  • Outputs a machine-readable JSON payload for downstream automation

Quick Start

Run the tool on a dataset to automatically choose and apply the appropriate statistical test and generate a comprehensive report.

Frequently Asked Questions about auto-stat-test

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automatically select the right statistical test for my dataset?▼

It automates statistical test selection by validating input, checking normality and variance, and applying the appropriate test for your dataset to deliver p-values and effect sizes.

What is the best way to compare non-normal data distributions for significance?▼

For non-normal data, the tool automatically selects non-parametric tests like Mann-Whitney to compare distributions, delivering p-values and plain-language interpretations.

Can I use pandas dataframes for multi-group ANOVA testing and get a JSON report?▼

Yes, it processes pandas dataframes to perform multi-group ANOVA testing and returns a structured JSON payload containing p-values, effect sizes, and plain-language interpretations.

Does this statistical testing tool output machine-readable JSON payloads?▼

Yes, it outputs a machine-readable JSON payload containing p-values, effect sizes, and plain-language interpretations to support downstream automation workflows.

What statistical tests are supported for two-group and multi-group comparisons?▼

It supports ANOVA for multi-group comparisons, Mann-Whitney for non-normal data, and Chi-square tests, automatically selecting the appropriate one based on data normality and variance.

When should I use chi-square tests instead of ANOVA for my data analysis?▼

Use chi-square tests for categorical data instead of ANOVA. The tool validates input data structure and automatically selects the appropriate test for your analysis.

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