Can this skill analyze large data files?

Yes, it follows best practices such as sampling large files for representative analysis and using specialized, high-performance Python libraries for processing.

What scientific domains are supported by this skill?

The skill covers six major categories: Chemistry/Molecular, Bioinformatics/Genomics, Microscopy/Imaging, Spectroscopy, Proteomics/Metabolomics, and General Scientific data formats.

What information is included in the generated EDA report?

Each report includes file metadata, format descriptions, data structure details, statistical summaries, quality assessments, and specific recommendations for downstream analysis.

Does this skill require additional software dependencies?

Many specialized formats require domain-specific libraries (like Biopython or RDKit); the skill will identify missing dependencies and provide installation instructions via uv or pip.

Scientific Exploratory Data Analysis

Name: Scientific Exploratory Data Analysis
Author: jimmc414

byjimmc414

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324

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数据科学与机器学习

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

This skill empowers Claude to act as an autonomous scientific data analyst, capable of identifying and inspecting complex datasets across domains such as chemistry, bioinformatics, imaging, and spectroscopy. It provides automated file type detection, deep metadata extraction, and rigorous data quality assessments for specialized formats including PDB, FASTA, ND2, and HDF5. By producing structured markdown reports with statistical summaries and actionable downstream recommendations, it significantly accelerates the initial discovery and preprocessing phases of scientific research.

主要功能

01324 GitHub stars

02Automated markdown report generation with statistical summaries and findings

03Context-aware recommendations for preprocessing and visualization tools

04Domain-specific analysis for chemistry, genomics, microscopy, and spectroscopy

05Automatic detection and analysis of 200+ specialized scientific file formats

06Comprehensive format-specific metadata extraction and integrity assessment

使用场景

01Rapidly assessing the quality and structure of experimental data files before starting deep analysis

02Identifying appropriate Python libraries and methods for processing obscure scientific file types

03Generating standardized documentation for complex research datasets in a reproducible format

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jimmc414/kosmos exploratory-data-analysis

For use in Claude.ai and ChatGPT

Download Skill