What problem does it solve? Creating technical diagrams that actually communicate structure and meaning is hard—most diagrams end up as labeled boxes that display information without teaching anything. This Skill guides the creation of Excalidraw JSON files that make visual arguments, with concrete evidence artifacts, multi-zoom architecture, and a mandatory render-and-validate loop. ## Core Features & Use Cases - Visual Pattern Library: Maps concepts to structural patterns (fan-out, convergence, timeline, tree, cycle) so the diagram's shape mirrors its meaning. - Evidence Artifacts: Embeds real code snippets, JSON examples, event names, and UI mockups into technical diagrams for educational value. - Section-by-Section Generation: Builds large diagrams incrementally to avoid output token limits and maintain quality. - Render & Validate Loop: Renders the JSON to PNG via a Python script and iterates on visual defects until the composition is correct. - Use Case: Ask for a diagram of a streaming protocol architecture, and receive an Excalidraw file showing real event names, connection code snippets, and a summary flow—rendered and visually verified. ## Quick Start Create an Excalidraw diagram visualizing how my application's frontend, API server, and database interact, including real request and response examples.
