If you work with AI image or video tools, you probably know this feeling:
You find a video reference that has the exact mood you want.
The lighting is right. The camera movement feels right. The pacing, color, composition, and atmosphere all match the idea in your head.
Then you open an AI tool and have to turn that video into a prompt.
That part is surprisingly annoying.
A video is full of useful information, but most of it is not obvious in plain language. You are not only describing the subject. You are describing the shot, the movement, the lens feeling, the lighting, the palette, the scene rhythm, and sometimes the visual grammar of a specific AI model.
I kept running into this while working with AI video and image workflows, so I built video to prompt to make that step easier.
The Problem Was Not Prompt Writing
At first, I thought the problem was simply that I needed to write better prompts.
But the real issue was consistency.
When I looked at a reference video, I could usually describe the obvious parts:
A person walking through a neon city at night.
But that prompt loses a lot of what makes the reference useful.
A better description might include:
A cinematic night street scene with a lone figure walking through rain-soaked pavement, neon reflections, shallow depth of field, handheld camera movement, soft haze, blue and magenta lighting, moody cyberpunk atmosphere, and dramatic urban composition.
That second version is much more useful because it captures how the scene is constructed, not just what appears in it.
The hard part is doing that repeatedly, especially when working across tools like Midjourney, Stable Diffusion, Sora, Runway, Kling, or other AI video platforms. Each model responds differently. Some need more camera language. Some need shorter visual descriptions. Some benefit from explicit motion cues.
So the question became:
Can a tool help extract the useful visual structure from a video and turn it into a reusable prompt draft?
What I Wanted the Tool to Do
I did not want to build a magic button that pretends to replace creative judgment.
The goal was more practical:
- Upload or submit a video reference.
- Analyze the visual content.
- Extract the important scene details.
- Generate a structured prompt that can be edited and reused.
- Make it easier to adapt that prompt to different AI tools.
The useful details usually include:
- Subject and visible action
- Environment and setting
- Camera angle and composition
- Lighting direction and intensity
- Color palette
- Motion and pacing
- Mood and atmosphere
- Cinematic or stylistic references
- Prompt-ready visual language
This kind of output gives creators a stronger starting point than a blank prompt box.
Prompt Extraction Is Different From Prompt Generation
One thing I learned while building this is that prompt extraction and prompt generation are not the same workflow.
Prompt generation usually starts from an idea.
For example:
Make a fantasy castle at sunset.
Prompt extraction starts from an existing visual reference.
The source video already contains decisions about framing, movement, color, texture, timing, and mood. The challenge is translating those decisions into language.
That translation layer is where many prompts become weak. If you only describe the objects in the scene, you miss the style. If you only describe the style, you may lose the action. If you ignore motion, the result may work for an image model but fail for a video model.
A good video-to-prompt workflow needs to preserve enough structure for the prompt to remain useful after editing.
A Practical Workflow
The workflow I use now looks like this:
- Collect a short reference video.
- Run it through the tool.
- Read the generated prompt as a first draft.
- Remove anything that does not match my intent.
- Add model-specific wording if needed.
- Save the strongest prompt versions for reuse.
That last step matters. Prompt work becomes much more useful when it compounds. A good extracted prompt can become part of a personal prompt library, a visual style guide, or a repeatable creative workflow.
What Is Still Imperfect
This is still an evolving product.
Some videos are easy to describe. Others are more complex. A fast montage, a heavily edited commercial, or a scene with multiple visual beats can require more structured output than a single cinematic shot.
There is also the question of formatting. A Midjourney-style prompt is not always the same as a Runway-style prompt. A Sora prompt may need stronger scene progression. A Stable Diffusion prompt may need more explicit visual tags.
So I am still improving areas like:
- Better scene breakdowns
- More model-aware prompt formats
- Cleaner camera and motion descriptions
- Better handling of complex or multi-shot videos
- More useful prompt history and reuse features
The tool is not finished in the sense that creative tools are never really finished. It is being shaped by real workflows.
Why I Think This Workflow Matters
AI generation is often discussed as if the main skill is typing a clever sentence.
In practice, a lot of the work is visual translation.
Creators already think in references: clips, frames, lighting examples, camera moves, styles, scenes, edits. The better we can translate those references into prompt language, the easier it becomes to build consistent outputs across AI tools.
That is the space I am trying to explore with Video to Prompt.
If you work with AI video, AI image generation, or prompt engineering, you can try it here:
Feedback is very welcome. You can reach me at support@video2prompt.io.
