Prompt Reverse-Engineer
Paste an AI output and get the prompt that likely created it — with platform-specific variations for text and image models.
Frequently asked questions
What does the prompt reverse-engineer do?+
You paste a sample of AI-generated text (or describe an AI-generated image), and the tool analyzes its style, structure, and tone to infer prompts that would likely produce similar output. For text you get minimal, detailed, and chain-of-thought prompt variants plus a system prompt guess; for images you get prompt versions tailored to Midjourney, DALL-E, Stable Diffusion, and Flux.
Can it recover the exact original prompt?+
No — that is not possible for any tool. Many different prompts can produce very similar outputs, so the result is an informed reconstruction, not a recovery. The confidence percentage indicates how strongly the output signals a particular prompting style. Treat the inferred prompts as a starting point and refine them through testing.
How do I reverse-engineer an image prompt?+
The tool works from a written description rather than an image upload. Switch to image mode and describe the picture in detail — subject, art style, lighting, composition, colors, and mood. The more specific your description, the closer the inferred prompts will be to something that reproduces the look.
Is my text sent to a server?+
Yes. Your input is sent to our server, where an AI model performs the analysis. Avoid pasting confidential documents or personal data — the tool only needs a representative sample of the output style, not the full sensitive content.
How reliable is the model family detection?+
The tool guesses whether the text came from a model family like GPT-4, Claude, or Gemini based on stylistic markers, but this is the least certain part of the analysis. Modern models overlap heavily in style, and edited or fine-tuned outputs blur the signals further, so treat the model guess as informed speculation.
Is this tool free?+
Yes, it is free to use with no signup. The only requirement is at least 20 characters of input, though longer samples give the analysis more signal to work with.