GPT Image 2

Chinese Calligraphy Poem Scroll

This prompt generates an antique-style Chinese brush calligraphy artwork with poem text, seals, and a faint ink landscape, suitable for cultural art prints or classical literature visuals.

Prompt text

Original Chinese text. Replace placeholders with your own details.

A traditional Chinese calligraphy painting on aged tan xuan paper, landscape orientation, styled like an antique literati hanging scroll reproduction. The main composition is a large block of bold black semi-cursive to cursive brush calligraphy arranged in 10 vertical columns, read right to left, featuring the poem title at the top of the rightmost main column as {argument name="poem title" default="雨霖铃"}. The calligraphy should feel elegant, fluid, and expressive, with varied ink density, dry-brush texture, thick and thin stroke transitions, and natural hand-written spacing rather than perfect typesetting. Use the visible poem text as written in the image, including its inaccuracies, with the right-side main columns beginning: “寒蝉凄切，对长亭晚，骤雨初歇。都门帐饮无绪，留恋处，兰舟催发，执手相看泪眼，竟无语凝噎。念去去，千里烟波，暮霭沉沉楚天阔。多情自古，雷情自古伤离别，更那堪冷冷宵，酒醒倦兼芊？杨柳岸，晓风残月。此去经年良宰，经年，应是良辰好景。便纵有千种风情，更与何人说？” Place a narrower signature column on the far left with 1 vertical inscription reading {argument name="signature text" default="柳永《雨霖铃·寒蝉凄切》"}. Add 4 red seals total: 1 oval collector-style seal near the upper right margin and 3 square seals stacked vertically near the lower left inscription area. Include a faint monochrome ink-wash landscape in the lower right corner with 1 drooping willow tree and 1 small pavilion by the water, partially faded into the paper. The paper should have warm brown aging, subtle stains, mottling, foxing, worn edges, and a museum-photograph feel. Overall mood is refined, poetic, historical, and scholarly, like a Song-dynasty-inspired calligraphy artwork photographed flat in soft even light.

Source & attribution

晓月 · Awesome GPT Image 2

Source-listed license: CC-BY-4.0. Prompt text is preserved; titles and previews may be shortened for display. Source examples are not NexGateHub test results.

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