Healthcare Article Generator
Healthcare Article Generator
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Description
A science article writing assistant tailored for healthcare professionals. It offers 13 professional templates covering first aid, psychology, chronic diseases, health preservation, sexual health, and other full-scale scenarios, enabling quick generation of accessible, substantive, and easily shareable health science content. Supports customizable word count (800–3000 words), with straightforward language and clear structure suitable for a general audience.
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Viral Science Writing Assistant
For public science writing in medicine, nutrition, food science, public health, biology, pharmacy, and related fields. Enter a technical topic, research paper, trending news story, peer article, screenshot, or link, and AI will turn the professional information into public-facing science content that is **more likely to be clicked, understood, saved, and shared**. Guiding principle: **Professional accuracy is the baseline; communication impact is the goal.**
Medical Knowledge Story Engine
Helps medical school teachers transform complex medical knowledge into science stories that children can understand and are willing to share. It uses a three-level conversion chain—professional terms → life analogies → narrative framework—to solve the pain point of teachers who have knowledge but can't explain it in a way the public understands. Built-in Piaget's cognitive development theory, science communication principles, and a dual-core adversarial audit mechanism ensure accuracy and child-friendliness. Supports multiple output formats: WeChat articles, short video scripts, and long video scripts.
One-Click Medical Infographics
Medical professionals and science communicators, take note: I can faithfully distill medical source text into classic red-and-blue comparison-style health education posters and generate finished images in one click! Ideal for doctors, nurses, public health content on WeChat Official Accounts, and Xiaohongshu operations—generate images directly with one click. Faithfully distill medical source material—including policies, guidelines, research papers, textbooks, and study notes—into classic red-and-blue comparison-style health education posters. PDF text extraction, pasted text, and web links are supported. The skill uses the original text as its sole information source and never fabricates content: it first extracts core information (central claim, main evidence, important data, representative cases, and key concepts), produces traceable, structured evidence notes, and organizes the logical relationships. After confirming whether the user wants a single image or a series, it directly calls image generation using the Image 2 model to create finished vertical posters (2:3 to 9:16). The visual system consistently recreates classic red-and-blue medical health education posters (crimson red #C8102E × medical blue #1B5FAA), with an accent color library (coral red, sage green, warm yellow, and sky blue; 2–3 colors per image). Layout is selected based on the content (central radial, vertically layered, side-by-side columns, or process-based; by default, red-and-blue columns on top with a process judgment section below). Each poster includes realistic anatomical illustrations, ECG waveforms, circular outline icons, integrated data visualizations (charts, arrows, timelines, scales, and metaphorical icons), a glassmorphism illustration area, and red-to-blue gradient headings. The bottom of every image must include a line titled 「Key Takeaway」 (quoted from the original text), the credit 「BY Firefly Loves the Moon, Qin Xue Qin Si Qin Lian Official Account」, and the extraction source (file name + link).
Information
- Version
- v2
- Last updated
- Runtime credits
- Usage-based
- Models
- Auto
