Exploratory Data Analysis

This prompts Claude to walk through the essential phases of exploratory data analysis: profiling your dataset, examining distributions, spotting relationships between variables, catching outliers, and assessing data quality. It's designed for that crucial stage before you start modeling when you need to actually understand what you're working with. The skill comes from aj-geddes' useful-ai-prompts repository, which has a decent following at 245 stars and passes all the security audits. It's straightforward prompt engineering rather than custom tooling, so your mileage depends on how well Claude interprets statistical questions about your specific dataset, but it gives you a solid framework to avoid jumping straight into analysis blind.