scientific-schematics

To generate scientific diagrams without hallucinated components, provide explicit method descriptions and enforce strict evidence grounding rules. The skill uses TODO placeholders for any missing evidence, ensuring your manuscript figures contain only verified technical components and causal arrows.

Yes, you can create neural network architecture schematics by providing text descriptions of your method pipelines or data-processing workflows. The skill converts your explicit input into structured figure schematics suitable for publication, preventing the addition of unverified architectural components.

The best way to build method pipeline flowcharts is to describe the stages and specify exactly which blocks and arrows to use. This evidence-aware approach produces manuscript-ready figure assets by mapping your training and evaluation protocols without inventing relationships.

When information is missing for workflow diagrams, the skill enforces anti-invention guardrails by inserting TODO placeholders rather than guessing. This ensures your system diagrams and flowcharts remain strictly grounded in the provided evidence before finalizing for venue formatting.

The tool produces manuscript-ready figure assets intended for documentation integration and provides follow-on handoffs for caption generation and venue formatting. It focuses on creating the structured figure schematics first, ensuring the technical accuracy needed before final publication formatting.