Overview
exploratory-data-analysis is an open-source data skill for Claude Code and compatible agents, published by K-Dense-AI. Its author describes it as: “Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage…”. The project has 34k stars on GitHub and is available under the MIT license. Add it to your setup with `git clone https://github.com/K-Dense-AI/scientific-agent-skills ~/.claude/skills/exploratory-data-analysis`.
What exploratory-data-analysis does
Use this skill to inspect **authorized local data** before modeling or confirmatory inference. It provides bounded, deterministic aggregate reports; it does not certify a file, infer scientific meaning, or support every format listed in the domain references.
What’s inside
The SKILL.md for exploratory-data-analysis is organised into these sections:
- Scope and non-negotiable boundary
- Version baseline (verified 2026-07-23)
- Exact capability matrix
- Safe local I/O contract
- Required EDA reasoning
- Workflow
- 1. Confirm authorization and root
- 2. Manifest before content analysis
- 3. Run the narrowest automated tool
- 4. Add scientific context
- 5. Create the report scaffold
- Output interpretation
Installation
Add exploratory-data-analysis to your agent with:
git clone https://github.com/K-Dense-AI/scientific-agent-skills ~/.claude/skills/exploratory-data-analysisReview a skill’s source before installing it — skills can instruct your agent to run commands. This command comes from the skill’s public repository, which is the source of truth for setup steps. New to skills? Read how to install Claude Code skills.
Supported agents
Neither the skill nor its repository names a specific agent. It uses the SKILL.md format, which several agents can load — check the repository for any agent-specific requirements.
License
exploratory-data-analysis is published under the MIT license.
Strengths
- Clear MIT license — safe to read and adapt within its terms
- Ships in K-Dense-AI/scientific-agent-skills, an established project with 33,821 GitHub stars
- Actively maintained — repository updated in the last 90 days
Author
Topics
Frequently asked questions
- What does exploratory-data-analysis do?
- Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain formats are reference-only and unknown formats fail closed.
- How do I install exploratory-data-analysis?
- Run git clone https://github.com/K-Dense-AI/scientific-agent-skills ~/.claude/skills/exploratory-data-analysis in your agent, then reload your skills. Review the source at https://github.com/K-Dense-AI/scientific-agent-skills before installing.
- Is exploratory-data-analysis free to use?
- Yes. exploratory-data-analysis is free and open source under the MIT license, so you can read, run, and adapt it within that license's terms.
- Where does exploratory-data-analysis come from?
- exploratory-data-analysis ships inside K-Dense-AI/scientific-agent-skills, a repository that contains 42 catalogued skills in total. The repository's 33,821 GitHub stars apply to that whole collection, not to this skill on its own.