rk_plotter

Name: rk_plotter
Availability: InStock
Author: rugkeypro

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

Updated Apr 1, 2026

Search Tags:#plotting #matplotlib #seaborn #data-visualization #publication #cartography #marine-ecology

Ready to run

npx skills add https://github.com/RugkeyPro/agent-skills --skill rk-plotter

💬 Prompt for ChatGPT / Claude Chat▼

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.