rk_plotter

Generate publication-quality marine ecology figures from datasets using Matplotlib, Cartopy, and Seaborn.

Updated Apr 1, 2026
One-click install
npx skills add https://github.com/RugkeyPro/agent-skills --skill rk-plotter
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: rk_plotter
Source: https://github.com/RugkeyPro/agent-skills/tree/main/rk_plotter
Command: npx skills add https://github.com/RugkeyPro/agent-skills --skill rk-plotter

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Marine scientists often struggle to convert raw marine data into clear, publication-quality figures rapidly, hindering communication of results.

Core Features & Use Cases

  • Templates and workflows for matplotlib, seaborn, and cartopy figures tailored to marine ecology data, including maps, time series, boxplots, and heatmaps.
  • One-script-per-figure workflow with per-panel export to SVG and PNG, ensuring editorial control and consistent styling.
  • Use cases include generating species distribution maps, seasonal time series, and SEM diagrams that adhere to GCB journal style.

Quick Start

Create a publication-ready marine-ecology plot from your latest dataset with rk_plotter and save outputs as SVG and PNG.

Frequently Asked Questions about rk_plotter

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

FAQPage Schema
How do I create publication-quality marine ecology plots from raw datasets?▼

Generate publication-quality marine ecology figures from datasets using Matplotlib, Cartopy, and Seaborn with project-wide styling. It supports creating species distribution maps, time-series plots, boxplots, heatmaps, and SEM diagrams with consistent color palettes and axis formatting.

What is the best way to generate species distribution maps for marine ecology journals?▼

The best way to generate species distribution maps for marine ecology journals is using Cartopy and Matplotlib templates tailored for marine data. This approach ensures editorial control with per-panel exports to SVG and PNG, adhering to GCB journal style conventions.

Does rk_plotter support exporting individual figure panels to SVG and PNG?▼

Yes, rk_plotter supports exporting individual figure panels to SVG and PNG. It operates on a one-script-per-figure workflow with per-panel export, ensuring you maintain editorial control and consistent styling across all generated marine ecology visualizations.

Can I use Matplotlib and Seaborn to create seasonal time-series plots for marine data?▼

Yes, you can use Matplotlib and Seaborn to create seasonal time-series plots for marine data. The workflow provides specific templates for time-series figures, applying project-wide styling and consistent color palettes to ensure publication-ready outputs.

Do I need a configuration module to maintain consistent styling across marine ecology figures?▼

Yes, you need the project's plot_config module to maintain consistent styling across marine ecology figures. This module provides the necessary figure directories, color definitions, and naming conventions required for the one-script-per-figure workflow.

Why does my marine ecology figure styling look inconsistent across different scripts?▼

Marine ecology figure styling looks inconsistent across different scripts when the project's plot_config module is not used. This module enforces project-wide figure directories, consistent color palettes, and naming conventions to ensure uniform axis formatting across all outputs.