How many file formats can it detect?

It can automatically identify and provide analysis strategies for over 200 different scientific file extensions, ranging from .pdb to .fastq and .czi.

Does this skill require external Python libraries?

Yes, depending on the format, it may recommend or use libraries like Biopython, RDKit, MDAnalysis, or Scanpy to perform deep inspections.

Which scientific fields does this skill support?

The skill provides comprehensive coverage for chemistry, bioinformatics, genomics, microscopy, spectroscopy, proteomics, metabolomics, and general scientific data.

Can it handle very large datasets?

For massive files, the skill is designed to analyze representative samples and metadata to provide insights without consuming excessive memory or time.

Scientific Exploratory Data Analysis

Name: Scientific Exploratory Data Analysis
Author: ricable

byricable

•

Data Science & ML

Performs automated exploratory data analysis and generates comprehensive markdown reports for over 200 scientific file formats.

This skill empowers researchers and developers to quickly understand the structure, quality, and content of complex scientific datasets by automating the exploratory data analysis (EDA) process. It supports a vast array of over 200 domain-specific formats—including bioinformatics, chemistry, microscopy, and spectroscopy—detecting file types automatically and producing detailed documentation. By providing statistical summaries, metadata extraction, and actionable downstream analysis recommendations, it streamlines the initial phase of scientific research and data processing within the Claude Code environment.

Key Features

01Comprehensive format-specific metadata extraction and quality assessment

02Actionable recommendations for preprocessing and downstream tools

03Automatic detection and analysis of 200+ scientific file formats

04Detailed markdown report generation including statistical summaries

051 GitHub stars

06Domain-specific analysis for chemistry, genomics, imaging, and spectroscopy

Use Cases

01Analyzing unknown scientific data files to determine internal structure and content

02Identifying appropriate Python libraries and methods for processing specific scientific extensions

03Generating standardized data quality reports before starting large-scale bioinformatics pipelines

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add ricable/ultimate-ai-agent exploratory-data-analysis

For use in Claude.ai and ChatGPT

Download Skill