Derived Play: Clause Transfer Rally
Create one polished public-gallery concept image titled exactly "Derived Play: Clause Transfer Rally". Output format: one vertica...
把 GPT Image 2 的复杂 prompt 拆成一张虚构地铁线路图:Subject、Setting、Relation、Style、Format、Safety、Revision 七条线在 Count Check、Text Check、Relation Hub、Aspect Gate、Source Credit 等站点换乘,用 missing relation、negation risk、fixed 和 PASS 9/10 做组合约束调试。

可参考这个示例来设计 Composition Benchmark、Information Visualization、Negation Risk、Prompt Clause Transit Map 工作流、提示词结构、视觉约束和结果检查方式。
Create one polished public-gallery concept image titled exactly "Use Case: Prompt Clause Transit Map". Output format: one ultra-wide 32:9 continuous information-visualization map, like a fictional subway system for prompt structure. It must be a single connected map, not a contact sheet, not a grid poster, not a physical object photo, not a tabletop game, not a storyboard, not a real transit map, not a city map. Scene: a clean editorial prompt-debugging wall display that turns a complex GPT Image prompt into transit lines. Seven colored lines cross and transfer through stations: "Subject Line", "Setting Line", "Relation Line", "Style Line", "Format Line", "Safety Line", "Revision Line". Transfer hubs are labeled "Count Check", "Text Check", "Relation Hub", "Aspect Gate", "Source Credit", and "Final Render". Small service-alert chips show "missing relation", "negation risk", and "fixed". The whole map is for a fictional project called "Lantern Orchard" using abstract icons only: a lantern icon, an orchard leaf icon, a river curve icon, and a blank image frame icon. Exact short readable text to render: "Use Case: Prompt Clause Transit Map", "Lantern Orchard", "Subject Line", "Setting Line", "Relation Line", "Style Line", "Format Line", "Safety Line", "Revision Line", "Count Check", "Text Check", "Relation Hub", "Aspect Gate", "Source Credit", "Final Render", "missing relation", "negation risk", "fixed", "PASS 9/10", "fictional only". Keep text short and legible; do not add long paragraphs or random placeholder text. Mechanism: demonstrate a GPT Image use case where prompt clauses become a route map for testing composition coverage. Each line represents one clause family; transfer hubs show where constraints interact; service alerts show failure modes; the final station shows a clean generated-output frame. Make it clear this is about prompt debugging, compositional evaluation, source attribution, and iteration planning. Visual style: crisp information design, high-end editorial data visualization, matte off-white background, graphite labels, distinct but restrained line colors in teal, amber, coral, slate, moss, indigo, and warm gray. Use precise station dots, route curves, tiny icons, and subtle UI chips. Balanced whitespace, professional typography, no purple-dominant gradient, no decorative orbs, no watermark. Safety and rights: fictional map and fictional project only, no real transit agency, no real city, no logos, no trademarks, no public figures, no politics, no dangerous instructions, no adult or explicit content, no gore or violence, no copyrighted characters, no living-artist style imitation, no source image reuse.
Create one polished public-gallery concept image titled exactly "Derived Play: Clause Transfer Rally". Output format: one vertica...
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