STEM Concept Four-Diagram Explainer Generator

The problem

STEM topics such as Fourier transforms, relativity, and black holes often break down when written for public accounts, class materials, or self-learners. Readers may recognize individual terms but miss why the phenomenon happens and where it is used. This skill avoids simply copying encyclopedia definitions. It reframes a concept as a readable image narrative: phenomenon first, then principle, core mechanism, and application, with Chinese annotations and plain-language notes to reduce reading load.

How it works

The skill uses a fixed four-diagram structure instead of generating loosely related images. Key steps include:
- Concept simplification: It sets explanation depth from concept_name and target_audience, such as general public, junior high students, or media readers.
- Four-diagram outline: It plans a logical progression through phenomenon, principle, mechanism, and use cases.
- Visual prompt generation: It creates prompts for each image with clear Chinese labels, visual focus, and preferred style.
- Async generation and polling: It submits a task via execute_task.py, receives a task_id, and polls with query_task.py until all four images complete.
- Integration and QA: It combines images, plain-language notes, logic summaries, and quality reports, then renders an HTML preview.

Boundaries

It fits science communication, educational slides, and simplified knowledge packaging. It is not intended for precise academic diagrams, formal derivations, or citation-ready data. Real calls require a ShowAPI appKey; without one, the system runs a simulated preview that is useful for checking style but should not be treated as production output. Quality scores are reference signals for plainness, logic, and Chinese clarity, and final content still needs manual review.