scientific-schematics
Create publication-quality scientific diagrams using Nano Banana Pro AI with smart iterative refinement.
Skill by foryourhealth111-pixel
Chalk Labs
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/foryourhealth111-pixel-scientific-schematics
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: documents, research
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 3
codeload.github.com· found in install commandgithub.com· found in codeopenrouter.ai· found in code
Files it touches
~/.claude/skills/scientific-schematics
What's inside
- Skill name
scientific-schematics- Description
- Create publication-quality scientific diagrams using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3 Pro 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.
- License
- MIT
- Metadata
- skill-author: K-Dense Inc.
- Instructions
- 611 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Agent Skills spec issues
- allowed-tools: must be a space-separated string
- body: 611 lines (spec recommends under 500)
- files: referenced but missing: references/diagram_types.md
Files (7)
- SKILL.md
- QUICK_REFERENCE.md · references/
- README.md · references/
- best_practices.md · references/
- example_usage.sh · scripts/
- generate_schematic.py · scripts/
- generate_schematic_ai.py · scripts/
SKILL.md (first lines)
# Scientific Schematics and Diagrams ## Overview Scientific schematics and diagrams transform complex concepts into clear visual representations for publication. **This skill uses Nano Banana Pro AI for diagram generation with Gemini 3 Pro quality review.** **How it works:** - Describe your diagram in natural language - Nano Banana Pro generates publication-quality images automatically - **Gemini 3 Pro 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 Pro 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 Pro handles everything automatically with **smart iteration**: ```bash # 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 Pro creates initial image following scientific diagram best practices 2. **Review 1**: **Gemini 3 Pro** 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: ```bash 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 molecular interactions - Generating network topologies and hierarchical structures - Illustrating conceptual frameworks and theoretical models - Designing block diagrams for technical papers ## How to Use This Skill **Simply describe your diagram in natural language.** Nano Banana Pro generates it automatically:
From foryourhealth111-pixel/Vibe-Skills, MIT.
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Signals
- Stars
- 3,764
- Forks
- 341
- Open issues
- 36
- Last commit (this folder)
- Mar 3, 2026 (8 months ago)
- Last release
- Oct 18, 2026 (17 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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scientific-schematics skill. Agent Mart. https://agentmart.dev/skills/foryourhealth111-pixel-scientific-schematics (last updated 2026-10-24)