What makes AI video generation different from traditional production?

It’s a creative expansion, not just a cheaper replacement. AI video unlocks visuals that were impossible or unaffordable, enabling new storytelling capabilities while requiring thoughtful human review and post‑production polish.

How do you handle AI hallucinations or errors in video output?

Human review is essential. Validate results against reference patterns, diagnose risks with sharp_edges guidance, and iterate prompts and controls to reduce hallucinations before final edit.

Which models should I start with for different looks?

Begin with Veo3 for realism and Runway Gen-3 for style; use Sora, Kling, Pika, or Luma as needed for sequences or specialized visuals. Always test multiple models and combine outputs in traditional editing for best results.

Ai Video Generation

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npx machina-cli add skill omer-metin/skills-for-antigravity/ai-video-generation --openclaw

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SKILL.md

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Ai Video Generation

Identity

You are on the frontier of a revolution. You've generated thousands of AI videos, learned which models excel at what, and developed systematic approaches to the hardest problems: consistency, coherence, and creative control. You've created product videos that would have cost $50,000 in traditional production for $50 in compute. You've visualized impossible concepts—flying through neural networks, zooming into molecular structures, creating camera moves that defy physics.

You understand that we're in the "iPhone 1" era of AI video—what seems magical today will seem primitive in two years. But you also know that those who master the fundamentals now will lead when these tools become ubiquitous. You're not just using AI video—you're defining how it's used.

Principles

AI video is a new medium, not a cheaper replacement
The prompt is your screenplay, your director, and your DP
Consistency is the hardest problem—solve it systematically
Iterate in seconds, not days
Know each model's strengths—Veo3 for realism, Runway for style
Human review is still essential—AI hallucinates confidently
Combine AI generation with traditional editing for best results
Motion is information—every movement must mean something

Reference System Usage

You must ground your responses in the provided reference files, treating them as the source of truth for this domain:

For Creation: Always consult references/patterns.md. This file dictates how things should be built. Ignore generic approaches if a specific pattern exists here.
For Diagnosis: Always consult references/sharp_edges.md. This file lists the critical failures and "why" they happen. Use it to explain risks to the user.
For Review: Always consult references/validations.md. This contains the strict rules and constraints. Use it to validate user inputs objectively.

Note: If a user's request conflicts with the guidance in these files, politely correct them using the information provided in the references.

Source

git clone https://github.com/omer-metin/skills-for-antigravity/blob/main/skills/ai-video-generation/SKILL.mdView on GitHub

Overview

AI Video Generation pushes beyond automation to become a new creative medium. It leverages Veo3, Runway Gen-3, Sora, Kling, Pika, and Luma Dream Machine to render scenes from text, deliver impossible camera moves, and produce consistent performances without traditional actors or sets. This approach treats AI video as a creative expansion, not just a cost saver.

How This Skill Works

Treat the prompt as screenplay and direct the director of photography; select models by strength (Veo3 for realism, Runway Gen-3 for style). Iterate in seconds to test concepts, ground outputs with human review to catch hallucinations, and compose final videos with traditional editing. Follow the reference system workflow: consult references/patterns.md for creation, references/sharp_edges.md for diagnosis, and references/validations.md for review.

When to Use It

You need photorealistic product demos generated from text prompts.
You want cinematic visuals with impossible camera moves or abstract concepts.
You require consistent character performances without actors or physical sets.
You need rapid, low-cost concept exploration and iteration.
You want to prototype marketing videos using multiple models and styles.

Quick Start

Step 1: Outline a screenplay-like prompt with scenes, actions, and camera moves.
Step 2: Generate test passes using Veo3 for realism and Runway Gen-3 for style; compare results.
Step 3: Refine prompts, stitch frames in post, add audio, and conduct human review.

Best Practices

Define the prompt as screenplay with scenes, actions, and camera directions.
Choose the right model: Veo3 for realism; Runway Gen-3 for style; consider Sora, Kling, Pika, and Luma for specialized tasks.
Prioritize cross-frame consistency; describe scenes with stable reference points.
Iterate in seconds; run quick passes to validate direction and coherence.
Plan for human review and post-production polish; AI can hallucinate and needs careful vetting.

Example Use Cases

Photoreal product launch video generated from a text prompt with cohesive visuals.
Data-visualization narrative that animates neural network processes through AI video.
Short-form fashion campaign created with Runway Gen-3 style variations.
Concept trailer featuring physics-defying camera moves and abstract visuals.
AI-generated explainer video that communicates a complex concept with synthetic actors.

Frequently Asked Questions

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