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Cinematographic prompt strategies for AI video generation

FreeFree tier
Type
Open Source
Company
ai-boost

About prompt

A comprehensive guide for crafting effective prompts for AI video generation tools, including Runway Gen 4.5, Kling 2.6, Veo 3/3.1, and Sora 2. It provides a universal prompt structure, vocabulary for shot types and camera movements, and model-specific strategies. The guide emphasizes specificity and cinematographic detail to achieve controlled video outputs.

Key Features

Universal prompt structure adaptable across models
Detailed shot type vocabulary (wide establishing, medium close-up, aerial, etc.)
Camera movement vocabulary (pan, tilt, dolly, truck, boom, etc.)
Model-specific strategies for Runway Gen 4.5, Kling 2.6, Veo 3/3.1, Sora 2
Guidance on lighting, environment, subject action, and duration hints
Core philosophy: treat prompt like a cinematographer's brief

Pros & Cons

Pros
  • Provides a structured, repeatable framework for video prompting
  • Covers multiple major AI video models in one guide
  • Includes specific terminology for shot types, camera moves, and lighting
  • Offers practical rules (e.g., one camera move + one action per shot)
Cons
  • Requires familiarity with filmmaking and cinematography terms
  • May need adaptation for models not explicitly covered
  • Guide is static; model capabilities evolve rapidly

Best For

Crafting prompts for AI video generation toolsImproving control and consistency in generated video clipsLearning cinematographic vocabulary for prompt engineeringExploring model-specific behaviors for optimal output

FAQ

What AI video models are covered in this guide?
The guide includes strategies for Runway Gen 4.5, Kling 2.6, Veo 3/3.1, and Sora 2, each described with a distinct personality (e.g., Runway as a kinetic sculptor, Sora as a physics simulator).
What is the core philosophy of the guide?
Treat a video prompt like a cinematographer's brief to a director, specifying what is happening, how the camera moves, what the light does, and when things change. Vagueness yields randomness, specificity yields control.
Does the guide include example prompts?
The file contains structured vocabulary and rules but not full example prompts; it focuses on the structure and components that should be included in a prompt.