Agent skill · Code Review & Quality

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.

LeonChaoXgithub.com/LeonChaoXGitHub ↗
claude-codecan modify filesships scriptsMIT
Install
npx skills add LeonChaoX/qinyan-academic-skills --skill scientific-schematics --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 7
SKILL.md size: 23 KB
Bundled scripts: yes
Allowed tools: ReadWriteEditBash
Path: skills/03-学术演示与可视化/scientific-schematics/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 759
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

Review
written from the skill's own SKILL.md · Aug 5, 2026

What it does

It instructs the agent to create publication-quality scientific diagrams by describing the diagram in natural language. It uses Nano Banana 2 AI to generate the image and Gemini 3.1 Pro Preview to review quality against a document-type threshold. It performs smart iteration: if the initial quality is below the threshold, it improves the prompt and regenerates until the score meets the threshold or max iterations are reached. Output includes versioned images stored under figures/ and a detailed review log with quality scores and critique.

How it works

  • Describe your diagram in natural language.
  • Nano Banana 2 generates the diagram image automatically.
  • Gemini 3.1 Pro Preview reviews quality against the specified document-type threshold.
  • If the score is greater than or equal to the threshold, the process stops (DONE).
  • If below threshold, the skill improves the prompt based on critique and regenerates the image.
  • The cycle repeats until the threshold is met or max iterations are reached.
  • Outputs include publication-ready images and a review log with quality scores and early-stop information.

When to use it

Use when you need neural network architectures, system diagrams, flowcharts, biological pathways, or complex scientific visualizations and require publication-quality diagrams with automated quality review and smart iteration.

What it can touch

  • It interacts with files and scripts as described in the examples:
    • scripts/generate_schematic.py
    • figures/ (output directory)
    • Optional environment variable OPENROUTER_API_KEY for API-based generation

Caveats

  • Thresholds vary by document type (e.g., journal 8.5/10, poster 7.0/10, presentation 6.5/10, default 7.5/10).
  • Regeneration occurs only if quality is below the threshold or max iterations have not been reached.
  • Outputs are versioned images and a detailed review log; no implied guarantees beyond the stated process.
From the SKILL.md

# 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

What's inside
Steps it walks through
  1. Overview
  2. Quick Start: Generate Any Diagram
  3. Configuration
  4. AI Generation Best Practices
  5. When to Use This Skill
  6. How to Use This Skill
  7. Smart Iterative Refinement Workflow
  8. How Smart Iteration Works
  9. Iteration 1: Initial Generation
  10. Quality Review by Gemini 3.1 Pro Preview
  11. Decision Point: Continue or Stop?
  12. Subsequent Iterations (Only If Needed)
  13. Review Log
  14. Advanced AI Generation Usage
Ships with 6 files
  • references/QUICK_REFERENCE.md
  • references/README.md
  • references/best_practices.md
  • scripts/example_usage.sh
  • scripts/generate_schematic.py
  • scripts/generate_schematic_ai.py
Commands it runs
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)
More from qinyan-academic-skills
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About this skill
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 LeonChaoX/qinyan-academic-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 LeonChaoX/qinyan-academic-skills, a repository with 759 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.

Keep going