scientific-schematics
Create publication-quality scientific diagrams using Nano Banana 2 AI with smart iterative refinement. Uses Gemini 3.1 Pro Preview for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.
npx skills add BioTender-max/awesome-bio-agent-skills --skill scientific-schematics --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Scientific Schematics and Diagrams ## Overview Scientific schematics and diagrams transform complex concepts into clear visual representations for publication. **This skill uses Nano Banana 2 AI for diagram generation with Gemini 3.1 Pro Preview quality review.** **How it works:** - Describe your diagram in natural language - Nano Banana 2 generates publication-quality images automatically - **Gemini 3.1 Pro Preview reviews quality** against document-type thresholds - **Smart iteration**: Only regenerates if quality is below threshold - Publication-ready output in minutes - No coding, templates, or manual drawing required **Quality Thresholds by Document Type:** | Document Type | Threshold | Description | |---------------|-----------|-------------| | journal | 8.5/10 | Nature, Science, peer-reviewed journals | | conference | 8.0/10 | Conference papers | | thesis | 8.0/10 | Dissertations, theses | | grant | 8.0/10 | Grant proposals | | preprint | 7.5/10 | arXiv, bioRxiv, etc. | | report | 7.5/10 | Technical reports | | poster | 7.0/10 | Academic posters | | presentation | 6.5/10 | Slides, talks | | default | 7.5/10 | General purpose | **Simply describe what you want, and Nano Bana
- Overview
- Quick Start: Generate Any Diagram
- Configuration
- AI Generation Best Practices
- When to Use This Skill
- How to Use This Skill
- Smart Iterative Refinement Workflow
- How Smart Iteration Works
- Iteration 1: Initial Generation
- Quality Review by Gemini 3.1 Pro Preview
- Decision Point: Continue or Stop?
- Subsequent Iterations (Only If Needed)
- Review Log
- Advanced AI Generation Usage
Generate for journal paper (highest quality threshold: 8.5/10) Generate for presentation (lower threshold: 6.5/10 - faster) python scripts/generate_schematic.py "Transformer encoder-decoder architecture showing multi-head attention" -o figures/transformer.png --doc-type presentation Generate for poster (moderate threshold: 7.0/10) python scripts/generate_schematic.py "MAPK signaling pathway from EGFR to gene transcription" -o figures/mapk_pathway.png --doc-type poster Custom max iterations (max 2) python scripts/generate_schematic.py "Complex circuit diagram with op-amp, resistors, and capacitors" -o figures/circuit.png --iterations 2 --doc-type journal export OPENROUTER_API_KEY='your_api_key_here' python scripts/generate_schematic.py "your diagram description" -o output.png Basic usage (default threshold 7.5/10)
What does the scientific-schematics skill do?
Create publication-quality scientific diagrams using Nano Banana 2 AI with smart iterative refinement. Uses Gemini 3.1 Pro Preview for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill scientific-schematics --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.