Cosmetic Serum Micro-Emulsion Droplet Swirl Macro
Microscopic macro photography of glistening hyaluronic acid serum droplets and golden botanical oil spheres suspended in crystal gel.
Compatibility & Specs

fluxDev 1.0
Style: product • Aspect Ratio: 1:1
dirty glass, air bubbles with dust, cartoon, greasy texture, opaque mud, oversaturated yellow
65 words • 480 characters
Customize Prompt
Fill in the variables below. Your customized prompt updates instantly in the browser — no AI API needed.
The cosmetic gel and oil formulation
How to Use This Prompt
Follow this 3-step workflow to extract high-signal responses from any compatible AI model.
1. Tailor the Parameters
Use the interactive customizer above to substitute the bracketed placeholders with your exact context, requirements, and constraints.
2. Send to AI Model
Copy the prompt and paste it into Claude, ChatGPT, Gemini, or Copilot. These models follow structured multi-step constraints reliably.
3. Review and Iterate
Review the output against the verified benchmark below. Follow up in the conversation to stress-test edge cases or refine tone.
Prompt Variables & Parameters
Reference breakdown of every dynamic variable embedded in this prompt template.
| Placeholder | Parameter Name | Type | Status | Description & Guidance |
|---|---|---|---|---|
| [serum_texture] | Serum Texture Formula | text | Required | The cosmetic gel and oil formulationDefault: a golden vitamin C and peptide facial serum swirl on a clear glass plate |
Example Execution & Benchmark Output
Sample input arguments and the verified AI response demonstrating expected quality and formatting.
Best Use Cases
Scenarios and roles where this prompt produces maximum leverage.
Tips for Best Results
Techniques to elevate response fidelity
- •Provide rich background context rather than one-sentence inputs to receive deep, non-generic responses.
- •Engage in multi-turn conversation: use the initial output as a baseline, then ask the AI to sharpen specific sections.
- •Prompt the model to highlight any hidden assumptions or missing trade-offs in its recommendations.
Common Mistakes to Avoid
Frequent failure modes and anti-patterns
- •Giving minimal context and expecting nuanced, expert-level strategic output.
- •Not validating factual references, citations, or statistical claims with verified primary sources.
- •Skipping the customization step and pasting raw bracketed template variables into the AI chat.
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