brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent,…
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
$ npx -y skills add xintaofei/codeg --skill scientific-schematics --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/scientific-schematicsContext 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
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 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:**
**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.
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:**
**Output**: Versioned images plus a detailed review log with quality scores, critiques, and early-stop information.
Set your OpenRouter API key:
export OPENROUTER_API_KEY='your_api_key_here'
Get an API key at: https://openrouter.ai/keys
**Effective Prompts for Scientific Diagrams:**
✓ **Good prompts** (specific, detailed):
✗ **Avoid vague prompts**:
**Key elements to include:**
**Scientific Quality Guidelines** (automatically applied):
This skill should be used when:
English | 简体中文 | 繁體中文 | 日本語 | 한국어 | Español | Deutsch | Français | Português | العربية Codeg (Code Generation) is a multi-agent coding workspace: run every AI coding agent in one place — and let them work together.
Repo: xintaofei/codeg
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent,…
Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical…
Use when completing tasks, implementing major features, or before merging to verify work meets requirements