Scientific exploratory data analysis

This skill guides defensive, human-led exploratory data analysis on scientific data. The agent does not open files and dump code; it captures problem context first, helps narrow to a single first step, takes instruction from the user, and asks "why?" before executing when the user requests a specific plot or table.

Usage

Use this skill when the user provides one or more data files (CSV, FASTA, or other scientific formats) and wants to explore or analyze them. Start by capturing context—do not load or plot data until the problem (biological, chemical, or data-science question) is clearly stated and the agent is aligned as a guided assistant.

Requirements

• uv for running Python scripts: every script uses PEP723 inline script metadata and is run with uv run script.py. Do not run ad-hoc Python or raw interpreters; each script declares and manages its own dependencies.
• Ability to read the relevant data formats (pandas, BioPython, etc.) via dependencies declared in the script block.

What It Does