scientific-schematics

Generate scientific diagrams from natural language prompts using Nano Banana 2 with Gemini quality review.

Updated Sep 2, 2026
One-click install
npx skills add https://github.com/ricfulop/cba-agentic-engineering-bootstrap --skill scientific-schematics-ricfulop
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scientific-schematics
Source: https://github.com/ricfulop/cba-agentic-engineering-bootstrap/tree/main/skills/scientific-schematics
Command: npx skills add https://github.com/ricfulop/cba-agentic-engineering-bootstrap --skill scientific-schematics-ricfulop

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, python-dotenv, and includes scripts (resource) and references (resource) components.

What problem does it solve? Creating publication-quality scientific diagrams (flowcharts, neural network architectures, biological pathways, circuit diagrams) normally requires manual drawing tools or coding, which is slow and demands design expertise. ## Core Features & Use Cases - Natural Language Generation: Describe a diagram in plain text and Nano Banana 2 generates a publication-ready PNG via the OpenRouter API. - Smart Iterative Refinement: Gemini 3.1 Pro Preview scores each image against document-type quality thresholds (8.5 for journals down to 6.5 for presentations) and only regenerates when below threshold. - Review Logging: Every run saves versioned images plus a JSON review log with scores, critiques, and early-stop reasons. - Use Case: Generate a CONSORT participant flow diagram for a clinical trial paper by describing the screening, exclusion, and randomization counts, then receive a journal-threshold-scored figure with a full review log. ## Quick Start Set the OPENROUTER_API_KEY environment variable and ask the agent to run scripts/generate_schematic.py with your diagram description, an output path, and a document type such as journal or poster.

Frequently Asked Questions about scientific-schematics

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate a scientific diagram from a text description?▼

Run scripts/generate_schematic.py with your diagram description, an output path via -o, and optionally a --doc-type flag. Nano Banana 2 generates the image through OpenRouter, and Gemini 3.1 Pro Preview reviews it against a quality threshold.

What API key do I need for AI diagram generation?▼

You need an OpenRouter API key set as the OPENROUTER_API_KEY environment variable, available at openrouter.ai/keys. You can also pass it with the --api-key flag or store it in a .env file.

How does the iterative quality review work?▼

Each generated image is scored 0-10 by Gemini 3.1 Pro Preview against a document-type threshold (8.5 for journal, 6.5 for presentation). If the score meets the threshold, generation stops early; otherwise the prompt is improved and regeneration occurs up to the iteration limit.

Why did my diagram generation fail with an API error?▼

Failures usually come from a missing or invalid OPENROUTER_API_KEY, a missing requests library, or API timeouts. Run with -v for verbose output showing the exact HTTP status and error detail returned by OpenRouter.

Should I use AI-generated figures for journal manuscripts?▼

No. The skill's CBA override states AI figures are for board slides and early review cartoons only. Final journal figures should be real data renderings produced via lib/styles.py, with AI diagrams reserved for presentations and drafts.