scientific-schematics

star 0

使用 Nano Banana 2 AI 和智能 iterative refinement 创建 publication-quality scientific diagrams。使用 Gemini 3.1 Pro Preview 进行 quality review。仅当质量低于你的 document type threshold 时重新生成。专长于 neural network architectures、system diagrams、flowcharts、biological pathways 和 complex scientific visualizations。

pomeloneo By pomeloneo schedule Updated 5/25/2026
play_arrow Run Skill in Manus View GitHub

name: scientific-schematics description: 使用 Nano Banana 2 AI 和智能 iterative refinement 创建 publication-quality scientific diagrams。使用 Gemini 3.1 Pro Preview 进行 quality review。仅当质量低于你的 document type threshold 时重新生成。专长于 neural network architectures、system diagrams、flowcharts、biological pathways 和 complex scientific visualizations。 allowed-tools: Read Write Edit Bash license: MIT license metadata: skill-author: K-Dense Inc.

Scientific Schematics and Diagrams

概述

Scientific schematics 和 diagrams 将复杂概念转化为适合发表的清晰 visual representations。此 skill 使用 Nano Banana 2 AI 生成 diagrams，并用 Gemini 3.1 Pro Preview 做 quality review。

工作方式：

  • 用自然语言描述 diagram
  • Nano Banana 2 自动生成 publication-quality images
  • Gemini 3.1 Pro Preview 会根据 document-type thresholds 审查质量
  • Smart iteration：仅当质量低于 threshold 时重新生成
  • 几分钟内获得 publication-ready output
  • 不需要 coding、templates 或手工绘图

按 Document Type 的 Quality Thresholds：

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 等
report 7.5/10 Technical reports
poster 7.0/10 Academic posters
presentation 6.5/10 Slides、talks
default 7.5/10 General purpose

只需描述你想要的内容，Nano Banana 2 就会创建它。 所有 diagrams 都存储在 figures/ 子文件夹，并在 papers/posters 中引用。

快速开始：生成任意 Diagram

只需描述 diagram，即可创建任意 scientific diagram。Nano Banana 2 会通过 smart iteration 自动处理所有步骤：

# 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

幕后发生的步骤：

  1. Generation 1：Nano Banana 2 遵循 scientific diagram best practices 创建初始 image
  2. Review 1：Gemini 3.1 Pro Preview 根据 document-type threshold 评估质量
  3. Decision：如果 quality >= threshold → DONE（不需要更多 iterations）
  4. 若低于 threshold：基于 critique 改进 prompt 并重新生成
  5. Repeat：直到质量达到 threshold 或达到 max iterations

Smart Iteration Benefits：

  • ✅ 如果第一次 generation 足够好，可节省 API calls
  • ✅ Journal papers 使用更高 quality standards
  • ✅ Presentations/posters turnaround 更快
  • ✅ 为每种 use case 匹配合适质量

Output：Versioned images，加上包含 quality scores、critiques 和 early-stop information 的详细 review log。

Configuration

设置 OpenRouter API key：

export OPENROUTER_API_KEY='your_api_key_here'

获取 API key：https://openrouter.ai/keys

AI Generation Best Practices

Scientific Diagrams 的有效 Prompts：

✓ Good prompts（具体、详细）：

  • "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"

✗ 避免模糊 prompts：

  • "Make a flowchart"（过于泛泛）
  • "Neural network"（哪种类型？哪些 components？）
  • "Pathway diagram"（哪个 pathway？哪些 molecules？）

需要包含的关键元素：

  • Type：Flowchart、architecture diagram、pathway、circuit 等
  • Components：要包含的具体元素
  • Flow/Direction：元素如何连接（left-to-right、top-to-bottom）
  • Labels：关键 annotations 或 text
  • Style：任何特定 visual requirements

Scientific Quality Guidelines（自动应用）：

  • Clean white/light background
  • High contrast 以保证 readability
  • 清晰、可读 labels（minimum 10pt）
  • Professional typography（sans-serif fonts）
  • Colorblind-friendly colors（Okabe-Ito palette）
  • 适当 spacing，防止 crowding
  • 适用时包含 scale bars、legends、axes

何时使用此 Skill

在以下情况应使用此 skill：

  • 创建 neural network architecture diagrams（Transformers、CNNs、RNNs 等）
  • 展示 system architectures 和 data flow diagrams
  • 为 study design 绘制 methodology flowcharts（CONSORT、PRISMA）
  • 可视化 algorithm workflows 和 processing pipelines
  • 创建 circuit diagrams 和 electrical schematics
  • 描绘 biological pathways 和 molecular interactions
  • 生成 network topologies 和 hierarchical structures
  • 展示 conceptual frameworks 和 theoretical models
  • 为 technical papers 设计 block diagrams

如何使用此 Skill

只需用自然语言描述 diagram。 Nano Banana 2 会自动生成：

python scripts/generate_schematic.py "your diagram description" -o output.png

就这样。 AI 会处理：

  • ✓ Layout and composition
  • ✓ Labels and annotations
  • ✓ Colors and styling
  • ✓ Quality review and refinement
  • ✓ Publication-ready output

适用于所有 diagram types：

  • Flowcharts（CONSORT、PRISMA 等）
  • Neural network architectures
  • Biological pathways
  • Circuit diagrams
  • System architectures
  • Block diagrams
  • 任意 scientific visualization

无需 coding、templates 或手工绘图。

AI Generation Mode（Nano Banana 2 + Gemini 3.1 Pro Preview Review）

Smart Iterative Refinement Workflow

AI generation system 使用 smart iteration：只有当 quality 低于你的 document type threshold 时才重新生成。

Smart Iteration 的工作方式

┌─────────────────────────────────────────────────────┐
│  1. Generate image with Nano Banana 2             │
│                    ↓                                │
│  2. Review quality with Gemini 3.1 Pro Preview                │
│                    ↓                                │
│  3. Score >= threshold?                             │
│       YES → DONE! (early stop)                      │
│       NO  → Improve prompt, go to step 1            │
│                    ↓                                │
│  4. Repeat until quality met OR max iterations      │
└─────────────────────────────────────────────────────┘

Iteration 1: Initial Generation

Prompt Construction：

Scientific diagram guidelines + User request

Output： diagram_v1.png

Quality Review by Gemini 3.1 Pro Preview

Gemini 3.1 Pro Preview 从以下方面评估 diagram：

  1. Scientific Accuracy（0-2 分）- 概念、notation、relationships 正确
  2. Clarity and Readability（0-2 分）- 易理解，hierarchy 清晰
  3. Label Quality（0-2 分）- labels 完整、可读、一致
  4. Layout and Composition（0-2 分）- logical flow、balanced、无 overlaps
  5. Professional Appearance（0-2 分）- publication-ready quality

Example Review Output：

SCORE: 8.0

STRENGTHS:
- Clear flow from top to bottom
- All phases properly labeled
- Professional typography

ISSUES:
- Participant counts slightly small
- Minor overlap on exclusion box

VERDICT: ACCEPTABLE (for poster, threshold 7.0)

Decision Point: Continue or Stop?

If Score... Action
>= threshold STOP - 对此 document type 已经足够好
< threshold 使用改进 prompt 进入下一 iteration

Example：

  • 对 poster（threshold 7.0）：Score 7.5 → 1 次 iteration 后 DONE
  • 对 journal（threshold 8.5）：Score 7.5 → 继续改进

Subsequent Iterations（仅在需要时）

如果 quality 低于 threshold，系统会：

  1. 从 Gemini 3.1 Pro Preview 的 review 中提取具体 issues
  2. 用 improvement instructions 增强 prompt
  3. 用 Nano Banana 2 重新生成
  4. 再次用 Gemini 3.1 Pro Preview 审查
  5. 重复直到达到 threshold 或 max iterations

Review Log

所有 iterations 都会保存到一个 JSON review log，其中包含 early-stop information：

{
  "user_prompt": "CONSORT participant flow diagram...",
  "doc_type": "poster",
  "quality_threshold": 7.0,
  "iterations": [
    {
      "iteration": 1,
      "image_path": "figures/consort_v1.png",
      "score": 7.5,
      "needs_improvement": false,
      "critique": "SCORE: 7.5\nSTRENGTHS:..."
    }
  ],
  "final_score": 7.5,
  "early_stop": true,
  "early_stop_reason": "Quality score 7.5 meets threshold 7.0 for poster"
}

注意： 使用 smart iteration 时，如果早期达到质量要求，可能只看到 1 次 iteration，而不是完整 2 次。

Advanced AI Generation Usage

Python API

from scripts.generate_schematic_ai import ScientificSchematicGenerator

# Initialize generator
generator = ScientificSchematicGenerator(
    api_key="your_openrouter_key",
    verbose=True
)

# Generate with iterative refinement (max 2 iterations)
results = generator.generate_iterative(
    user_prompt="Transformer architecture diagram",
    output_path="figures/transformer.png",
    iterations=2
)

# Access results
print(f"Final score: {results['final_score']}/10")
print(f"Final image: {results['final_image']}")

# Review individual iterations
for iteration in results['iterations']:
    print(f"Iteration {iteration['iteration']}: {iteration['score']}/10")
    print(f"Critique: {iteration['critique']}")

Command-Line Options

# Basic usage (default threshold 7.5/10)
python scripts/generate_schematic.py "diagram description" -o output.png

# Specify document type for appropriate quality threshold
python scripts/generate_schematic.py "diagram" -o out.png --doc-type journal      # 8.5/10
python scripts/generate_schematic.py "diagram" -o out.png --doc-type conference   # 8.0/10
python scripts/generate_schematic.py "diagram" -o out.png --doc-type poster       # 7.0/10
python scripts/generate_schematic.py "diagram" -o out.png --doc-type presentation # 6.5/10

# Custom max iterations (1-2)
python scripts/generate_schematic.py "complex diagram" -o diagram.png --iterations 2

# Verbose output (see all API calls and reviews)
python scripts/generate_schematic.py "flowchart" -o flow.png -v

# Provide API key via flag
python scripts/generate_schematic.py "diagram" -o out.png --api-key "sk-or-v1-..."

# Combine options
python scripts/generate_schematic.py "neural network" -o nn.png --doc-type journal --iterations 2 -v

Prompt Engineering Tips

1. 明确 Layout：

✓ "Flowchart with vertical flow, top to bottom"
✓ "Architecture diagram with encoder on left, decoder on right"
✓ "Circular pathway diagram with clockwise flow"

2. 包含 Quantitative Details：

✓ "Neural network with input layer (784 nodes), hidden layer (128 nodes), output (10 nodes)"
✓ "Flowchart showing n=500 screened, n=150 excluded, n=350 randomized"
✓ "Circuit with 1kΩ resistor, 10µF capacitor, 5V source"

3. 指定 Visual Style：

✓ "Minimalist block diagram with clean lines"
✓ "Detailed biological pathway with protein structures"
✓ "Technical schematic with engineering notation"

4. 要求 Specific Labels：

✓ "Label all arrows with activation/inhibition"
✓ "Include layer dimensions in each box"
✓ "Show time progression with timestamps"

5. 提及 Color Requirements：

✓ "Use colorblind-friendly colors"
✓ "Grayscale-compatible design"
✓ "Color-code by function: blue for input, green for processing, red for output"

AI Generation Examples

Example 1: CONSORT Flowchart

python scripts/generate_schematic.py \
  "CONSORT participant flow diagram for randomized controlled trial. \
   Start with 'Assessed for eligibility (n=500)' at top. \
   Show 'Excluded (n=150)' with reasons: age<18 (n=80), declined (n=50), other (n=20). \
   Then 'Randomized (n=350)' splits into two arms: \
   'Treatment group (n=175)' and 'Control group (n=175)'. \
   Each arm shows 'Lost to follow-up' (n=15 and n=10). \
   End with 'Analyzed' (n=160 and n=165). \
   Use blue boxes for process steps, orange for exclusion, green for final analysis." \
  -o figures/consort.png

Example 2: Neural Network Architecture

python scripts/generate_schematic.py \
  "Transformer encoder-decoder architecture diagram. \
   Left side: Encoder stack with input embedding, positional encoding, \
   multi-head self-attention, add & norm, feed-forward, add & norm. \
   Right side: Decoder stack with output embedding, positional encoding, \
   masked self-attention, add & norm, cross-attention (receiving from encoder), \
   add & norm, feed-forward, add & norm, linear & softmax. \
   Show cross-attention connection from encoder to decoder with dashed line. \
   Use light blue for encoder, light red for decoder. \
   Label all components clearly." \
  -o figures/transformer.png --iterations 2

Example 3: Biological Pathway

python scripts/generate_schematic.py \
  "MAPK signaling pathway diagram. \
   Start with EGFR receptor at cell membrane (top). \
   Arrow down to RAS (with GTP label). \
   Arrow to RAF kinase. \
   Arrow to MEK kinase. \
   Arrow to ERK kinase. \
   Final arrow to nucleus showing gene transcription. \
   Label each arrow with 'phosphorylation' or 'activation'. \
   Use rounded rectangles for proteins, different colors for each. \
   Include membrane boundary line at top." \
  -o figures/mapk_pathway.png

Example 4: System Architecture

python scripts/generate_schematic.py \
  "IoT system architecture block diagram. \
   Bottom layer: Sensors (temperature, humidity, motion) in green boxes. \
   Middle layer: Microcontroller (ESP32) in blue box. \
   Connections to WiFi module (orange box) and Display (purple box). \
   Top layer: Cloud server (gray box) connected to mobile app (light blue box). \
   Show data flow arrows between all components. \
   Label connections with protocols: I2C, UART, WiFi, HTTPS." \
  -o figures/iot_architecture.png

Command-Line Usage

生成 scientific schematics 的主要入口：

# Basic usage
python scripts/generate_schematic.py "diagram description" -o output.png

# Custom iterations (max 2)
python scripts/generate_schematic.py "complex diagram" -o diagram.png --iterations 2

# Verbose mode
python scripts/generate_schematic.py "diagram" -o out.png -v

注意： Nano Banana 2 AI generation system 在 iterative refinement process 中包含 automatic quality review。每次 iteration 都会评估 scientific accuracy、clarity 和 accessibility。

Best Practices Summary

Design Principles

  1. Clarity over complexity - 简化并移除不必要元素
  2. Consistent styling - 使用 templates 和 style files
  3. Colorblind accessibility - 使用 Okabe-Ito palette 和 redundant encoding
  4. Appropriate typography - Sans-serif fonts，minimum 7-8 pt
  5. Vector format - Publication 始终使用 PDF/SVG

Technical Requirements

  1. Resolution - 优先 vector，或 raster 使用 300+ DPI
  2. File format - LaTeX 用 PDF，web 用 SVG，PNG 作为 fallback
  3. Color space - Digital 用 RGB，print 用 CMYK（需要时转换）
  4. Line weights - Minimum 0.5 pt，典型 1-2 pt
  5. Text size - Final size 下 minimum 7-8 pt

Integration Guidelines

  1. Include in LaTeX - 对生成 images 使用 \includegraphics{}
  2. Caption thoroughly - 描述所有 elements 和 abbreviations
  3. Reference in text - 在 narrative flow 中解释 diagram
  4. Maintain consistency - Paper 中所有 figures 保持同一 style
  5. Version control - 将 prompts 和 generated images 保存在 repository

Troubleshooting Common Issues

AI Generation Issues

Problem：Text 或 elements overlap

  • Solution：AI generation 会自动处理 spacing
  • Solution：提高 iterations：--iterations 2 以获得更好 refinement

Problem：Elements 连接不正确

  • Solution：让 prompt 对 connections 和 layout 更具体
  • Solution：增加 iterations 以获得更好 refinement

Image Quality Issues

Problem：Export quality poor

  • Solution：AI generation 会自动生成 high-quality images
  • Solution：增加 iterations 获得更好结果：--iterations 2

Problem：生成后 elements overlap

  • Solution：AI generation 会自动处理 spacing
  • Solution：增加 iterations：--iterations 2 以获得更好 refinement
  • Solution：让 prompt 对 layout 和 spacing requirements 更具体

Quality Check Issues

Problem：False positive overlap detection

  • Solution：调整 threshold：detect_overlaps(image_path, threshold=0.98)
  • Solution：在 visual report 中手动 review flagged regions

Problem：Generated image quality is low

  • Solution：AI generation 默认生成 high-quality images
  • Solution：增加 iterations 获得更好结果：--iterations 2

Problem：Colorblind simulation shows poor contrast

  • Solution：在 code 中显式切换到 Okabe-Ito palette
  • Solution：添加 redundant encoding（shapes、patterns、line styles）
  • Solution：增加 color saturation 和 lightness differences

Problem：High-severity overlaps detected

  • Solution：查看 overlap_report.json 获取 exact positions
  • Solution：增加这些 specific regions 的 spacing
  • Solution：使用调整后的参数重新运行并再次 verify

Problem：Visual report generation fails

  • Solution：检查 Pillow 和 matplotlib installations
  • Solution：确保 image file 可读：Image.open(path).verify()
  • Solution：检查是否有足够 disk space 生成 report

Accessibility Problems

Problem：Colors 在 grayscale 中不可区分

  • Solution：运行 accessibility checker：verify_accessibility(image_path)
  • Solution：添加 patterns、shapes 或 line styles 作为 redundancy
  • Solution：增加 adjacent elements 间的 contrast

Problem：打印时 text 太小

  • Solution：运行 resolution validator：validate_resolution(image_path)
  • Solution：按 final size 设计，使用 minimum 7-8 pt fonts
  • Solution：在 resolution report 中检查 physical dimensions

Problem：Accessibility checks 持续失败

  • Solution：查看 accessibility_report.json 获取具体 failures
  • Solution：将 color contrast 至少提高 20%
  • Solution：Finalizing 前用实际 grayscale conversion 测试

Resources and References

Detailed References

加载这些文件以获取特定主题的完整信息：

  • references/best_practices.md - Publication standards 和 accessibility guidelines

External Resources

Python Libraries

Publication Standards

与其他 Skills 的集成

此 skill 可与以下 skill 协同使用：

  • Scientific Writing - Diagrams 遵循 figure best practices
  • Scientific Visualization - 共享 color palettes 和 styling
  • LaTeX Posters - 为 poster presentations 生成 diagrams
  • Research Grants - 为 proposals 生成 methodology diagrams
  • Peer Review - 评估 diagram clarity 和 accessibility

Quick Reference Checklist

提交 diagrams 前验证：

Visual Quality

  • High-quality image format（AI generation 输出 PNG）
  • 无 overlapping elements（AI 自动处理）
  • 所有 components 间 spacing 充分（AI 优化）
  • Clean、professional alignment
  • 所有 arrows 正确连接到 intended targets

Accessibility

  • 使用 colorblind-safe palette（Okabe-Ito）
  • Grayscale 中可用（用 accessibility checker 测试）
  • Elements 间 contrast 充分（已验证）
  • 适当使用 redundant encoding（shapes + colors）
  • Colorblind simulation 通过所有 checks

Typography and Readability

  • Final size 下 text minimum 7-8 pt
  • 所有 elements 清晰、完整标注
  • Font family 和 sizing 一致
  • 无 text overlaps 或 cutoffs
  • 适用时包含 units

Publication Standards

  • 与 manuscript 中其他 figures 保持 consistent styling
  • Caption 完整，所有 abbreviations 已定义
  • 在 manuscript text 中适当引用
  • 满足 journal-specific dimension requirements
  • 按 journal 要求导出格式（PDF/EPS/TIFF）

Quality Verification（Required）

  • 运行 run_quality_checks() 并达到 PASS status
  • 审查 overlap detection report（zero high-severity overlaps）
  • 通过 accessibility verification（grayscale 和 colorblind）
  • Target DPI 下 resolution validated（print 为 300+）
  • Visual quality report 已生成并审查
  • 所有 quality reports 与 figure files 一起保存

Documentation and Version Control

  • Source files（.tex、.py）已保存，便于 future revision
  • Quality reports 已归档到 quality_reports/ directory
  • Configuration parameters 已记录（colors、spacing、sizes）
  • Git commit 包含 source、output 和 quality reports
  • README 或 comments 解释如何 regenerate figure

Final Integration Check

  • Figure 在 compiled manuscript 中显示正确
  • Cross-references 正常（\ref{} 指向正确 figure）
  • Figure number 与 text citations 匹配
  • Caption 出现在相对 figure 正确的页面
  • 无与 figure 相关的 compilation warnings 或 errors

Environment Setup

# Required
export OPENROUTER_API_KEY='your_api_key_here'

# Get key at: https://openrouter.ai/keys

Getting Started

最简单用法：

python scripts/generate_schematic.py "your diagram description" -o output.png

使用此 skill 创建清晰、accessible、publication-quality diagrams，以有效传达复杂 scientific concepts。带 iterative refinement 的 AI-powered workflow 可确保 diagrams 符合 professional standards。

Install via CLI
npx skills add https://github.com/pomeloneo/obsidian --skill scientific-schematics
Repository Details
star Stars 0
call_split Forks 0
navigation Branch main
article Path SKILL.md
Occupations
Fine Artists Including Painters Sculptors And Illustrators
More from Creator
pomeloneo
pomeloneo Explore all skills →