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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

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Install
$ npx -y skills add xintaofei/codeg --skill scientific-schematics --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/scientific-schematics

Context preview

The summary Claude sees to decide when to auto-load this skill.

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

SKILL.md

scientific-schematics.SKILL.md
name: scientific-schematics
description: 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.
allowed-tools: Read Write Edit Bash
license: MIT license
required_environment_variables: [{"name": "OPENROUTER_API_KEY", "prompt": "OpenRouter API key for the skill's LLM-powered steps.", "required_for": "optional features"}]
metadata: {"version": "1.1", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for the skill's LLM-powered steps."}]}}

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 Banana 2 creates it.** All diagrams are stored in the figures/ subfolder and referenced in papers/posters.

Quick Start: Generate Any Diagram

Create any scientific diagram by simply describing it. Nano Banana 2 handles everything automatically with **smart iteration**:

# Generate for journal paper (highest quality threshold: 8.5/10)
python scripts/generate_schematic.py "CONSORT participant flow diagram with 500 screened, 150 excluded, 350 randomized" -o figures/consort.png --doc-type journal

# 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

**What happens behind the scenes:** 1. **Generation 1**: Nano Banana 2 creates initial image following scientific diagram best practices 2. **Review 1**: **Gemini 3.1 Pro Preview** evaluates quality against document-type threshold 3. **Decision**: If quality >= threshold → **DONE** (no more iterations needed!) 4. **If below threshold**: Improved prompt based on critique, regenerate 5. **Repeat**: Until quality meets threshold OR max iterations reached

**Smart Iteration Benefits:**

  • ✅ Saves API calls if first generation is good enough
  • ✅ Higher quality standards for journal papers
  • ✅ Faster turnaround for presentations/posters
  • ✅ Appropriate quality for each use case

**Output**: Versioned images plus a detailed review log with quality scores, critiques, and early-stop information.

Configuration

Set your OpenRouter API key:

export OPENROUTER_API_KEY='your_api_key_here'

Get an API key at: https://openrouter.ai/keys

AI Generation Best Practices

**Effective Prompts for Scientific Diagrams:**

✓ **Good prompts** (specific, detailed):

  • "CONSORT flowchart showing participant flow from screening (n=500) through randomization to final analysis"
  • "Transformer neural network architecture with encoder stack on left, decoder stack on right, showing multi-head attention and cross-attention connections"
  • "Biological signaling cascade: EGFR receptor → RAS → RAF → MEK → ERK → nucleus, with phosphorylation steps labeled"
  • "Block diagram of IoT system: sensors → microcontroller → WiFi module → cloud server → mobile app"

✗ **Avoid vague prompts**:

  • "Make a flowchart" (too generic)
  • "Neural network" (which type? what components?)
  • "Pathway diagram" (which pathway? what molecules?)

**Key elements to include:**

  • **Type**: Flowchart, architecture diagram, pathway, circuit, etc.
  • **Components**: Specific elements to include
  • **Flow/Direction**: How elements connect (left-to-right, top-to-bottom)
  • **Labels**: Key annotations or text to include
  • **Style**: Any specific visual requirements

**Scientific Quality Guidelines** (automatically applied):

  • Clean white/light background
  • High contrast for readability
  • Clear, readable labels (minimum 10pt)
  • Professional typography (sans-serif fonts)
  • Colorblind-friendly colors (Okabe-Ito palette)
  • Proper spacing to prevent crowding
  • Scale bars, legends, axes where appropriate

When to Use This Skill

This skill should be used when:

  • Creating neural network architecture diagrams (Transformers, CNNs, RNNs, etc.)
  • Illustrating system architectures and data flow diagrams
  • Drawing methodology flowcharts for study design (CONSORT, PRISMA)
  • Visualizing algorithm workflows and processing pipelines
  • Creating circuit diagrams and electrical schematics
  • Depicting biological pathways and
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