scientific-schematics

Generate publication-quality scientific diagrams from natural-language prompts.

1|Updated Apr 8, 2026
One-click install
npx skills add https://github.com/brainworkup/skills --skill scientific-schematics-brainworkup
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: scientific-schematics
Source: https://github.com/brainworkup/skills/tree/main/neuropsych-reports/references/luria-related-complement-skills/scientific-schematics
Command: npx skills add https://github.com/brainworkup/skills --skill scientific-schematics-brainworkup

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, and includes references (resource) components.

What problem does it solve?

Automates the creation of publication-quality scientific diagrams from natural-language prompts, eliminating the tedious drafting and formatting toil.

Core Features & Use Cases

  • AI-driven diagram generation for neural networks, system architectures, biological pathways, and other complex scientific visuals.
  • Smart iterative refinement with Gemini 3.1 Pro Preview to ensure publication-ready outputs.
  • Document-type thresholds that govern regeneration, guaranteeing outputs match journal standards or presentation needs.

Quick Start

Describe your diagram in natural language to generate a publication-ready schematic.

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?

You can generate publication-quality scientific diagrams by providing natural-language prompts describing your visualization. The AI automates drafting and formatting to produce outputs ready for journals or presentations.

Can I create biological pathways and neural network architectures using AI?

Yes, AI-driven diagram generation supports neural networks, system architectures, biological pathways, and other complex scientific visuals from your text descriptions.

How does iterative refinement work for scientific visualization?

Iterative refinement uses Gemini 3.1 Pro Preview to review AI-generated scientific visualizations. It enforces document-type thresholds and regenerates diagrams only when quality falls below target standards.

What's the best way to ensure my AI-generated diagrams meet journal standards?

The tool applies document-type thresholds governing regeneration to guarantee outputs match journal standards. Gemini 3.1 Pro Preview reviews quality, ensuring publication-ready schematics automatically.

Does this scientific visualization tool support color accessibility?

Yes, color-accessibility is enforced during the AI-generation process. The iterative refinement ensures complex scientific visualizations meet accessibility standards required for publication.

What are the limitations of using Nano Banana 2 for scientific schematics?

Nano Banana 2 AI generates the initial scientific schematics, but relies on Gemini 3.1 Pro Preview for quality review. If outputs fall below document-type thresholds, it regenerates to meet publication needs.