What problem does it solve?
This Skill addresses systemic biases and stereotypical outputs in image and video generation models by providing prompt architectures, negative constraints, and review processes that ensure human subjects are depicted with cultural specificity, dignity, and physical realism.
Core Features & Use Cases
- Annotated Prompt Architectures: Decomposes prompts into Subject, Action, Context, Camera, Style, and Negative Constraints to reduce model exoticism and tokenism.
- Negative-Prompt Libraries: Explicit exclusions for cloned faces, gibberish or invented scripts, hero-symbol compositions, and other common generative artifacts.
- Temporal Physics & Motion Constraints: Defines how clothing, hair, and mobility aids should behave across frames for video generation to avoid glitches in Runway, Sora, or similar models.
- Post-Generation QA: A review gate and checklist focused on sociological accuracy, community validation, and artifact elimination for production-ready assets.
- Use Cases: Inclusive campaign imagery, culturally accurate event visuals, accessible motion media (mobility aids), and cross-model asset continuity (image-to-animation).
Quick Start
Create an inclusive video prompt describing a 45-year-old Black female executive leading a strategy session in Nairobi with explicit negative constraints forbidding cloned faces, gibberish text, and oversized cultural symbols.
