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exploratory-data-analysis

Detect scientific file formats and generate markdown EDA reports.

Updated May 26, 2026
Search Tags:#bioinformatics#scientific data#quality assessment#eda#microscopy#markdown report#format detection
One-click install
npx skills add https://github.com/XWIlluDelu/agent-share --skill exploratory-data-analysis-xwilludelu
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: exploratory-data-analysis
Source: https://github.com/XWIlluDelu/agent-share/tree/main/lib/exploratory-data-analysis
Command: npx skills add https://github.com/XWIlluDelu/agent-share --skill exploratory-data-analysis-xwilludelu

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Scientists often struggle to quickly understand unfamiliar scientific files—what format they are, what data they contain, whether the data quality looks trustworthy, and what analyses should come next—without manually hunting through documentation and writing one-off parsers.

Core Features & Use Cases

  • Automatic file type detection across 200+ scientific formats to route you to the right parsing strategy.
  • Format-specific metadata extraction and analysis using curated reference documentation and category-aware logic for bioinformatics, chemistry, microscopy, spectroscopy, proteomics/metabolomics, and general scientific data.
  • Quality assessment and downstream recommendations by producing a detailed markdown report that includes data structure summaries, key findings, and suggested next steps.

Quick Start

Ask the skill to analyze your file path and output an EDA markdown report, for example: "Run exploratory data analysis on /path/to/experiment_data.fastq and save the report to experiment_data_eda_report.md."

Frequently Asked Questions about exploratory-data-analysis

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

FAQPage Schema
How do I generate an exploratory data analysis report for scientific files?▼

To generate an exploratory data analysis report, provide the path to your scientific file and request a markdown report. The skill automatically detects the format, extracts metadata, assesses quality, and outputs a structured markdown summary.

Can I run exploratory data analysis on microscopy and genomics files without knowing their exact format?▼

Yes, you can run exploratory data analysis on microscopy and genomics files without knowing the format. The skill automatically detects over 200 scientific formats and applies category-specific logic to extract metadata and assess quality.

What's the best way to assess data quality before downstream bioinformatics analysis?▼

The best way to assess data quality is to generate a structured markdown report. The skill evaluates your bioinformatics files, extracts format-specific metrics, and provides suggested next steps to ensure dataset understanding before downstream analysis.

Does this exploratory data analysis tool support spectroscopy and proteomics data formats?▼

Yes, this exploratory data analysis tool supports spectroscopy and proteomics data formats. It routes files across genomics, chemistry, microscopy, spectroscopy, and metabolomics to category-aware parsing logic to extract relevant scientific metadata.

How does format detection work for general scientific array and table data?▼

Format detection for general scientific array and table data works by reading file extensions to route to the correct parsing strategy. It optionally loads relevant reference documentation to perform category-specific analysis and render a markdown report.

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