exploratory-data-analysis

exploratory-data-analysis is a skill for Claude Code, Codex from eric861129/SKILLS_All-in-one. It costs 89 tokens per session (3,336 once invoked), scanned A, a copy of exploratory-data-analysis, MIT.

A tool for examining scientific data files, including files from many research and technical formats, before deeper analysis.

In plain words
What is it for?
Use it to identify file types, extract metadata, summarize distributions, assess data quality, and plan follow-up analyses.
Why use it?
It helps you understand unfamiliar data and spot missing, invalid, or incomplete information before relying on it.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to identify file types, extract metadata, summarize distributions, assess data quality, and plan follow-up analyses.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/eric861129/skills_all-in-one/exploratory-data-analysis
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add eric861129/SKILLS_All-in-one --skill exploratory-data-analysis
Clone the repo
git clone --depth 1 https://github.com/eric861129/SKILLS_All-in-one

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for exploratory-data-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/eric861129/skills_all-in-one/exploratory-data-analysis/github.svg)](https://agentmods.dev/skills/eric861129/skills_all-in-one/exploratory-data-analysis)
Your own site
<a href="https://agentmods.dev/skills/eric861129/skills_all-in-one/exploratory-data-analysis"><img src="https://agentmods.dev/badge/skills/eric861129/skills_all-in-one/exploratory-data-analysis/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for exploratory-data-analysis

Your own site · 80×15
<a href="https://agentmods.dev/skills/eric861129/skills_all-in-one/exploratory-data-analysis"><img src="https://agentmods.dev/badge/skills/eric861129/skills_all-in-one/exploratory-data-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 89 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,336 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00089 $0.03336
Opus 5 $0.00044 $0.01668
Sonnet 5 $0.00018 $0.00667
Haiku 4.5 $0.00009 $0.00334

Measured 9d ago against content hash 8084fae57c4c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

exploratory-data-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/eda_analyzer.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to exploratory-data-analysis — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

public/SKILLS/Data & Analysis/exploratory-data-analysis/SKILL.md · 445 lines

How it starts

The opening of the file, as written. The whole thing — 445 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Exploratory Data Analysis

Overview

Perform comprehensive exploratory data analysis (EDA) on scientific data files across multiple domains. This skill provides automated file type detection, format-specific analysis, data quality assessment, and generates detailed markdown reports suitable for documentation and downstream analysis planning.

Key Capabilities:

  • Automatic detection and analysis of 200+ scientific file formats
  • Comprehensive format-specific metadata extraction
  • Data quality and integrity assessment
  • Statistical summaries and distributions
  • Visualization recommendations
  • Downstream analysis suggestions
  • Markdown report generation

When to Use This Skill

Use this skill when:

  • User provides a path to a scientific data file for analysis
  • User asks to "explore", "analyze", or "summarize" a data file
  • User wants to understand the structure and content of scientific data
  • User needs a comprehensive report of a dataset before analysis
  • User wants to assess data quality or completeness
  • User asks what type of analysis is appropriate for a file

Supported File Categories

The skill has comprehensive coverage of scientific file formats organized into six major categories:

1. Chemistry and Molecular Formats (60+ extensions)

Structure files, computational chemistry outputs, molecular dynamics trajectories, and chemical databases.

File types include: .pdb, .cif, .mol, .mol2, .sdf, .xyz, .smi, .gro, .log, .fchk, .cube, .dcd, .xtc, .trr, .prmtop, .psf, and more.

Reference file: references/chemistry_molecular_formats.md

2. Bioinformatics and Genomics Formats (50+ extensions)

Sequence data, alignments, annotations, variants, and expression data.

File types include: .fasta, .fastq, .sam, .bam, .vcf, .bed, .gff, .gtf, .bigwig, .h5ad, .loom, .counts, .mtx, and more.

Reference file: references/bioinformatics_genomics_formats.md

3. Microscopy and Imaging Formats (45+ extensions)

Microscopy images, medical imaging, whole slide imaging, and electron microscopy.

Read the full file on GitHub · 445 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 445 lines · 89 tokens per session scan A 8084fae57c4c

Subscribe to this mod's changes

exploratory-data-analysis is a skill published in the GitHub repository eric861129/SKILLS_All-in-one (52 stars, last pushed 4mo ago), licensed MIT. It adds 89 tokens to every session and 3,336 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to exploratory-data-analysis, differing in 0 lines, and is treated as a copy.

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