scientific-schematics

Generate scientific diagrams from natural language descriptions using Nano Banana 2 AI.

Updated Jun 6, 2026
One-click install
npx skills add https://github.com/Ritabrata-Chakraborty/Claude-Setup --skill scientific-schematics-ritabrata-chakraborty
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: scientific-schematics
Source: https://github.com/Ritabrata-Chakraborty/Claude-Setup/tree/main/skills/scientific-schematics
Command: npx skills add https://github.com/Ritabrata-Chakraborty/Claude-Setup --skill scientific-schematics-ritabrata-chakraborty

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, requests[files], numpy, opencv-python, matplotlib, schemdraw, Pillow, base64, json, ast, sys, os, time, re, json, shutil, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps create clear, accessible, publication-quality diagrams by using natural language descriptions.

Core Features & Use Cases

  • Diagram Generation: Create a wide range of scientific diagrams, including neural network architectures, biological pathways, system diagrams, and more.
  • Iterative Refinement: Uses AI to generate initial diagrams and then iteratively refine them based on quality metrics and human feedback.
  • Quality Standards: Adheres to scientific standards and colorblind accessibility for wider reach.

Quick Start

Use the scientific-schematics skill to generate a "Transformer neural network architecture diagram with multi-head attention".

Frequently Asked Questions about scientific-schematics

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

FAQPage Schema
How do I generate publication-quality scientific diagrams from natural language descriptions?

Yes, you can generate neural network architecture diagrams using natural language prompts. The tool specifically accommodates complex scientific visualizations like Transformer models with multi-head attention and refines them to meet publication-quality standards.

What is the best way to create biological pathways and flowcharts that meet colorblind accessibility standards?

The best way to create accessible biological pathways is through AI generation that inherently adheres to colorblind accessibility standards. This ensures wider reach and scientific accuracy without requiring manual color adjustments.

Do I need an OpenRouter API key and Python environment to create system diagrams with AI?

Yes, you need an OpenRouter API key and a Python environment to create system diagrams with AI. These prerequisites are required to run the underlying Nano Banana 2 AI for generation and Gemini 3.1 Pro Preview for quality review.

Can I iteratively refine scientific visualizations based on quality metrics and human feedback?

Yes, you can iteratively refine scientific visualizations based on quality metrics and human feedback. The generation process uses an AI model to review the initial outputs and apply improvements until the diagrams meet the desired scientific standards.

Does this AI diagram generation approach work with Python libraries like matplotlib and schemdraw?

Yes, this AI diagram generation approach works with Python libraries like matplotlib and schemdraw. The underlying environment utilizes these libraries alongside OpenCV and Pillow to process, render, and output the complex scientific visualizations.