exploratory-data-analysis

You can automate exploratory data analysis by providing a scientific data file to the AI. The Skill detects the format, extracts metadata, performs quality checks, and generates a Markdown report with actionable recommendations.

Generating an EDA report for scientific data is handled by automatic file type detection and type-specific analysis routing. The Skill processes formats across genomics, spectroscopy, and chemistry to assess structure and output a consolidated Markdown report.

Yes, you can analyze a dataset folder to produce a consolidated report for project stakeholders. The workflow identifies formats, extracts key metadata, and generates detailed Markdown summaries to guide downstream analysis.

Automated data discovery supports HDF5 and image files through its underlying dependencies. It automatically detects these formats among 200+ scientific types, extracting metadata and performing quality checks.

Metadata extraction and quality checks work by automatically detecting file formats and routing them to type-specific analysis. This assesses the data structure and quality before generating recommendations in a Markdown report.

Automated EDA focuses on initial inspection, metadata extraction, and quality assessment rather than executing full downstream analysis. It generates actionable recommendations to guide subsequent processing rather than completing the final analysis itself.