
Young Woman in Sequin Dress on Stairs
An editorial portrait prompt of a young woman in a shimmering dress sitting on a wooden staircase.
This is a gpt-image-2 prompt case for 人像角色. Use the copy-ready prompt below to generate similar visuals, and review Awesome Nano Banana Pro Prompts attribution plus commercial-use rights before reuse.
Need the full prompt set? Use the 人像角色 topic hub for more related examples, or open the GPT Image 2 prompt library for the full example index, reusable structures, and source attribution.
Prompt
Copy-ready prompt
Vertical 2:3 ratio.{argument name="subject" default="young women"} She sat on a modern wooden staircase, her hair in a messy updo. She was dressed {argument name="dress" default="A shimmering silver halter-neck sequined dress"} She wears silver high-heeled sandals. Her legs are crossed. She wears silver heart-shaped earrings. Each ankle is adorned with a magenta bracelet. Her expression is alluring, her lips slightly parted. The background consists of blurred vertical wooden planks and black metal railings. Please do not alter the face.Prompt variables
Editable argument placeholders found in the prompt, with their default values.
Variable
subject
Default
young women
Variable
dress
Default
A shimmering silver halter-neck sequined dress
More cases in this category
Prioritized by category, input mode compatibility, quality, and lower risk.
Reuse and source notes
Use this prompt safely after previewing the case.
- 1.Copy the prompt or open it directly in Dovoo with the generation button.
- 2.Adjust variables, aspect ratio, and reference images for your own use case.
- 3.Before publishing or paid usage, verify source rights, attribution requirements, and brand or likeness risks.
Can I use this prompt commercially?
Commercial-use status is restricted. Review the original source, license, brand constraints, and legal requirements before paid usage.
Where does this case come from?
This case is imported from Awesome Nano Banana Pro Prompts; keep attribution visible and check the source URL before reuse.





