distribution-profiler

Name: distribution-profiler
Availability: InStock
Author: ai-analyst-lab

Profile numeric column distributions and generate diagnostic reports with A/B testing guidance.

16|7|Updated Apr 1, 2026

Search Tags:#diagnostics #statistics #distribution #ab-testing #data-profiling #test-selection #normality

Ready to run

npx skills add https://github.com/ai-analyst-lab/ai-analyst-plus --skill distribution-profiler

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: distribution-profiler
Source: https://github.com/ai-analyst-lab/ai-analyst-plus/tree/main/.claude/skills/distribution-profiler
Command: npx skills add https://github.com/ai-analyst-lab/ai-analyst-plus --skill distribution-profiler

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Profile the distribution of numeric data to prevent wrong test selections and to guide robust analytics, providing actionable diagnostics and an A/B testing playbook.

Core Features & Use Cases

Identify the distribution of a numeric column (continuous or count) and surface summary statistics.
Recommend appropriate statistical tests and transformations, with explicit caveats for skew, zero-inflation, and multimodality.
Produce a structured diagnostic report and an accompanying 4-panel visualization to inform analysis workflows.

Quick Start

Ask me to profile the distribution of a numeric column to start the analysis.

Frequently Asked Questions about distribution-profiler

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

FAQPage Schema

How do I determine the distribution of a numeric metric before A/B testing?▼

Data profiling requires a numeric column from raw data, derived metrics, or per-user aggregates to analyze distribution characteristics. Providing a clean numeric dataset ensures the diagnostic report accurately identifies skew, modality, and zero-inflation for test selection.

What statistical tests should I use for non-normal data with skew or zero-inflation?▼

For non-normal data with skew or zero-inflation, the profiler evaluates distribution diagnostics and explicitly recommends appropriate statistical tests while providing caveats and suitable data transformations to guide robust analysis.

How do I profile discrete versus continuous data distributions?▼

To profile discrete versus continuous data distributions, the profiler distinguishes the data type and applies appropriate aggregation level checks to surface modality, zero-inflation, and normality test guidance for accurate experimental design.

What is the best way to select appropriate statistical tests based on my data distribution?▼

The best way to select appropriate statistical tests is to run a distribution profile that identifies normality and bimodality, delivering a structured diagnostic report and an A/B testing playbook tailored to your specific data characteristics.

Can I use data profiling diagnostics for per-user aggregates in experimental design?▼

Yes, you can use data profiling diagnostics for per-user aggregates in experimental design. The profiler applies checks at the appropriate aggregation level and produces an A/B testing playbook to guide robust experimental setup and analysis.