Description
scientific-visualization is an agent skill for creating and auditing truthful, accessible, publication-ready scientific figures with Matplotlib, Seaborn or Plotly. It is for figure design, multi-panel layouts and the checks that come before submission. The skill puts scientific meaning first, before appearance. It keeps universal principles apart from dated publisher rules, preserves the raw data and every transformation, uses colour redundantly so that it does not rely on hue alone, and inspects the delivered files rather than trusting plotting defaults. Its guardrails are strict. It never alters, hides, invents or selectively enhances data to improve a figure. It keeps raw tables, exclusions, missing-value codes, analysis code, normalisation, binning, image adjustments and random seeds. It does not assume a journal's requirements, but identifies the exact journal, article type, figure type and submission stage, and checks the live official guidance. It warns that a palette, a DPI value or an automated report does not by itself make a figure accessible or compliant. It also says that interactive hover is not a substitute for labels, alt text or a static fallback.…
Highlights
- Figures in Matplotlib, Seaborn or Plotly
- Never alters or hides data
- Keeps raw data, exclusions and seeds
- Redundant colour and accessibility checks
- Checks delivered files, not defaults
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scientific-visualization FAQ
What is the first principle?
Preserve scientific meaning before optimising appearance. The skill never alters or selectively enhances data.
Does a palette make a figure accessible?
Not by itself. The skill says no palette, DPI value or automated report establishes accessibility or compliance.
How should journal rules be handled?
The skill asks you to identify the exact journal, article type, figure type and stage, and to check live guidance.
Is interactive output enough?
No. The skill says hover is not a substitute for labels, alt text, keyboard access or a static fallback.
How do I install it?
Run npx skills add https://github.com/k-dense-ai/scientific-agent-skills --skill scientific-visualization.
Is it checked for security?
Its security audits show passes from Gen Agent Trust Hub, Socket and Snyk.
What are the best scientific-visualization alternatives?
Popular alternatives to scientific-visualization include matplotlib, seaborn and power-bi-report-design-consultation. See all scientific-visualization alternatives