Video-to-Prompt System Design

If your team still writes prompts from scratch, you're wasting your best visual source: real video references.

A modern AI video workflow should convert every useful clip into a reusable prompt package. That package should include:

• A concise scene summary
• A robust master prompt
• A short execution prompt for fast generation
• A negative prompt to avoid artifacts
• A shot list that captures camera logic
• A keyword set for indexing and retrieval

Why this matters

Without structure, prompt quality becomes random and hard to scale. With a structured package, teams can:

1. Reproduce style faster
2. Align editors, creators, and operators
3. Build a searchable prompt library
4. Reduce iteration cost per deliverable

Recommended package format

Use a fixed schema so every output is directly usable:

{
  "summary": "...",
  "masterPrompt": "...",
  "shortPrompt": "...",
  "negativePrompt": "...",
  "keywords": ["..."],
  "shots": ["..."]
}

Operational best practices

• Keep masterPrompt expressive and production-level
• Keep shortPrompt under platform limits
• Keep negativePrompt focused on common failure modes
• Keep shots ordered by sequence or narrative progression
• Keep keywords concise for downstream indexing

Final takeaway

Treat video-to-prompt as a system, not a one-off generation trick. Once every clip becomes structured prompt data, your creative output becomes faster, more consistent, and easier to scale.