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HolobiomicsLab
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exploratory-data-analysis

Detect scientific file types and generate markdown EDA reports with quality metrics.

4|1|Updated Jun 18, 2025
Search Tags:#statistics#eda#data-quality#metadata-extraction#multiformat#report-generation#scientific-data
One-click install
npx skills add https://github.com/HolobiomicsLab/Toolomics --skill exploratory-data-analysis-holobiomicslab
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: exploratory-data-analysis
Source: https://github.com/HolobiomicsLab/Toolomics/tree/main/mcp_host/skills/scientific-skills/scientific-skills/exploratory-data-analysis
Command: npx skills add https://github.com/HolobiomicsLab/Toolomics --skill exploratory-data-analysis-holobiomicslab

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires numpy, pandas, biopython, h5py, Pillow, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Automatically detects and analyzes scientific data files across 200+ formats, extracting metadata, assessing quality, and generating actionable markdown reports to accelerate research workflows.

Core Features & Use Cases

  • Automatic file-type detection and format-specific metadata extraction across 200+ formats
  • Domain-aware exploratory data analysis with basic statistics, QC metrics, and recommendations
  • Markdown report generation suitable for documentation, publication, and downstream analysis

Quick Start

Provide the path to a data file to generate a complete EDA report in markdown.

Frequently Asked Questions about exploratory-data-analysis

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

FAQPage Schema
How do I run an exploratory data analysis on scientific data files with unknown formats?▼

To run exploratory data analysis on scientific data, provide the file path to automatically detect its format, extract metadata, and generate a structured markdown report with quality metrics and actionable recommendations.

Can I use this tool to extract metadata from bioinformatics and microscopy files?▼

Yes, you can extract metadata from bioinformatics and microscopy files. The tool applies domain-aware analysis across diverse scientific formats including chemistry, proteomics, metabolomics, and spectroscopy data.

What is the best way to assess data quality across multiple scientific formats automatically?▼

The best way to assess data quality across scientific formats is using auto-EDA, which detects file types, calculates quality control metrics, and outputs a structured markdown report with actionable recommendations.

Does this EDA tool support HDF5 and image files processed with h5py and Pillow?▼

Yes, this EDA tool supports HDF5 and image files. It uses h5py and Pillow dependencies to handle diverse scientific formats, ensuring comprehensive metadata extraction and basic statistics generation.

How do I generate a markdown report for publication from raw spectroscopy data?▼

You generate a markdown report for publication by processing raw spectroscopy data through the auto-EDA pipeline, which produces a structured filename_eda_report.md containing metadata, quality metrics, and recommendations.

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