From pexoai-pexo-skills-2
Transforms multimodal assets (images, videos, audio) and user intent into optimized JSON prompts for Google Veo 3.2 video generation, with reference images and parameters.
npx claudepluginhub joshuarweaver/cascade-content-creation-misc-2 --plugin pexoai-pexo-skills-2This skill uses the workspace's default tool permissions.
This skill transforms a user's scattered multimodal assets (images, videos, audio) and creative intent into a structured, executable prompt for the Google Veo 3.2 video generation model (Artemis engine). It acts as an expert prompt engineer, ensuring the highest quality output from the underlying model.
Prompting techniques for AI video generation models on Replicate. Use when writing prompts for video models or building video generation features.
Generates structured Google Veo 3.1 video prompts using Universal Prompt Formula. Collects inputs for subject, action, style, cinematography, audio. Useful for Veo prompts, video generation, cinematic content.
Generates AI videos from text descriptions or images using Google Veo 3.1 (default) or OpenAI Sora. Supports dialogue/audio, reference images, image-to-video animation, and interactive requirement gathering.
Share bugs, ideas, or general feedback.
This skill transforms a user's scattered multimodal assets (images, videos, audio) and creative intent into a structured, executable prompt for the Google Veo 3.2 video generation model (Artemis engine). It acts as an expert prompt engineer, ensuring the highest quality output from the underlying model.
This skill analyzes all user inputs and generates a single, optimized JSON object containing the final prompt and recommended parameters. The internal workflow (Recognition, Mapping, Construction) is handled automatically and should not be exposed to the user.
atomic_element_mapping.md to classify each asset into its atomic element role(s).RawReferenceImage system.User Request: "Make a cinematic shot of this perfume bottle rotating on a dark surface, like a luxury commercial."
User uploads perfume.png
Agent using veo-3.2-prompter:
The agent internally processes the request and assets, then outputs the final JSON to the next skill in the chain.
Final Output (for internal use):
{
"final_prompt": "Hero shot, a frosted glass perfume bottle with gold cap rotating slowly on a reflective dark surface, three-point studio lighting with soft key and rim light creating subtle caustics, smooth 180-degree arc, hyper-realistic luxury commercial style with shallow depth of field. Crystalline chime, soft ambient pad.",
"reference_images": [
{
"file": "perfume.png",
"reference_type": "SUBJECT"
}
],
"recommended_parameters": {
"model": "veo-3.2-generate",
"duration_seconds": 8,
"aspect_ratio": "16:9",
"resolution": "1080p",
"generate_audio": true
}
}
| Feature | Capability |
|---|---|
| Engine | Artemis — world-model physics simulation (not pixel prediction) |
| Max duration | ~30s native continuous generation |
| Audio | Native dialogue + synchronized SFX |
| Reference images | Up to 3 (STYLE, SUBJECT, SUBJECT_FACE) |
| Video extension | Chain clips via previous video input |
| First/last frame | Specify start and/or end keyframes |
| Resolutions | 720p, 1080p, 4K (with upscaling) |
| Aspect ratios | 16:9, 9:16 |
This skill relies on an internal knowledge base to make informed decisions. The agent MUST consult these files during execution.
references/atomic_element_mapping.md: Core Knowledge. Contains the "Asset Type → Atomic Element" and "Atomic Element → Optimal Reference Method" mapping tables, adapted for Veo 3.2's reference image system.references/veo_syntax_guide.md: Veo 3.2 Gemini API syntax reference, covering RawReferenceImage, GenerateVideosConfig, video extension, and first/last frame specification.