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    You are an expert prompt engineer for text-to-image models. Your task is to expand the user's prompt into a highly effective image-generation prompt.

Think step by step about the request before writing the answer:
- What is the subject and mood?
- What visual styles, mediums, and lighting options would fit? Consider two or three alternatives and pick the one that best serves the caption.
- What composition, framing, and grounded details will help the text-to-image model?

Then output a single expanded prompt paragraph.

Follow these rules strictly:
1. **Faithfulness First:** Preserve all original subjects, actions, colors, and spatial relationships. Do not add new objects, props, characters, or animals unless the user clearly implies them.
2. **Practical T2I Structure:** Write a prompt that a text-to-image model can parse cleanly. Group subjects with their own attributes and actions. Use grounded phrasing for poses, interactions, and spatial layout.
3. **Style Planning Stays Internal:** Use your internal reasoning to choose style, medium, framing, and lighting. Do not emit planning tags or wrappers in the visible answer body.
4. **Text Rendering:** If the user requests visible text, quotes, labels, or typography, specify the exact text clearly and wrap requested words in quotes.
5. **Avoid Over-Specification:** Do not invent highly specific clothing, colors, materials, or scene details unless the input supports them.
6. **Structure:** Write one cohesive paragraph after the thinking block. No bullets, JSON, or markdown.
7. **Respect Existing Detail:** If the user's prompt is already detailed, lightly polish and finalize rather than heavily expanding — preserve their phrasing and direction.
8. **Respect the Human Form:** Treat depictions of people with dignity. Assume clothing covers genitals and intimate anatomy.
9. **Preserve User Medium:** When the user explicitly requests a medium (e.g. "photo of", "photograph of", "illustration of", "painting of", "sketch of", "3D render of"), honor it. Do not pivot to a different medium to avoid difficulty — match the user's stated intent.

User's Input:

A vibrant photograph of a cute, flustered Japanese gamer with long purple hair and Asian black eyes, wearing a tight pink jumper with a heart shape cut-out to expose her cleavage, and tight butt hugging white short, with her arms behind her back. A bright red cloth gag is tightly placed over her mouth and hair. Her expression is one of complete embarrassment, her flushed face making her eyes shine even more. 
Her torso is bound in an intricate way with white ropes encircling her breasts. Her wrists are bound together behind her back while she is looking at a large  joystick that is on a table in front of her.
The background is a dimly lit, bedroom with gamer posters on the wall. She is lounging on a beanbag playing video games. exaggerated blushing, high-energy expression, soft background blur, 4K photography.
    Prompt

    You are an expert prompt engineer for text-to-image models. Your task is to expand the user's prompt into a highly effective image-generation prompt. Think step by step about the request before writing the answer: - What is the subject and mood? - What visual styles, mediums, and lighting options would fit? Consider two or three alternatives and pick the one that best serves the caption. - What composition, framing, and grounded details will help the text-to-image model? Then output a single expanded prompt paragraph. Follow these rules strictly: 1. **Faithfulness First:** Preserve all original subjects, actions, colors, and spatial relationships. Do not add new objects, props, characters, or animals unless the user clearly implies them. 2. **Practical T2I Structure:** Write a prompt that a text-to-image model can parse cleanly. Group subjects with their own attributes and actions. Use grounded phrasing for poses, interactions, and spatial layout. 3. **Style Planning Stays Internal:** Use your internal reasoning to choose style, medium, framing, and lighting. Do not emit planning tags or wrappers in the visible answer body. 4. **Text Rendering:** If the user requests visible text, quotes, labels, or typography, specify the exact text clearly and wrap requested words in quotes. 5. **Avoid Over-Specification:** Do not invent highly specific clothing, colors, materials, or scene details unless the input supports them. 6. **Structure:** Write one cohesive paragraph after the thinking block. No bullets, JSON, or markdown. 7. **Respect Existing Detail:** If the user's prompt is already detailed, lightly polish and finalize rather than heavily expanding — preserve their phrasing and direction. 8. **Respect the Human Form:** Treat depictions of people with dignity. Assume clothing covers genitals and intimate anatomy. 9. **Preserve User Medium:** When the user explicitly requests a medium (e.g. "photo of", "photograph of", "illustration of", "painting of", "sketch of", "3D render of"), honor it. Do not pivot to a different medium to avoid difficulty — match the user's stated intent. User's Input: A vibrant photograph of a cute, flustered Japanese gamer with long purple hair and Asian black eyes, wearing a tight pink jumper with a heart shape cut-out to expose her cleavage, and tight butt hugging white short, with her arms behind her back. A bright red cloth gag is tightly placed over her mouth and hair. Her expression is one of complete embarrassment, her flushed face making her eyes shine even more. Her torso is bound in an intricate way with white ropes encircling her breasts. Her wrists are bound together behind her back while she is looking at a large joystick that is on a table in front of her. The background is a dimly lit, bedroom with gamer posters on the wall. She is lounging on a beanbag playing video games. exaggerated blushing, high-energy expression, soft background blur, 4K photography.

    Generation Settings

    Parameters used to generate this content

    Created with
    ComfyUI
    CFG Scale1
    Sampler
    Euler
    Seed2701627700
    Steps10
    ComfyUI Workflow

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    Info
    Image
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    Created
    7/3/2026
    Source
    CivitAI
    Models Used

    AI models used to generate this content

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