veo-3.2-prompter

Original：🇺🇸 English

Translated

Expert prompt engineering for Google Veo 3.2 (Artemis engine). Use when the user wants to generate a video with Veo 3.2, needs help crafting cinematic prompts, or mentions Veo, Google video generation, or Artemis engine.

2installs

Sourcepexoai/pexo-skills

Added on2026-03-20

NPX Install

npx skill4agent add pexoai/pexo-skills veo-3.2-prompter

SKILL.md Content

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Veo 3.2 Prompt Designer Skill

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.

When to Use

When the user provides assets (images, videos, audio) for video generation with Veo 3.2.
When the user's request is complex and requires careful prompt construction for the Veo model.
When using any Google Veo 3.x model for video generation.

Core Function

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.

Internal Workflow

Phase 1: Recognition — Analyze uploaded assets and user intent. Use the
```
atomic_element_mapping.md
```
to classify each asset into its atomic element role(s).
Phase 2: Mapping — For each atomic element, determine the optimal reference method (reference image, text prompt, or hybrid). Use the mapping table to decide.
Phase 3: Construction — Assemble the final prompt using the 5-Part Framework (Shot → Subject → Environment → Camera → Style) and attach reference images via the Gemini API's
```
RawReferenceImage
```
system.

Usage Example

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):

json

{
  "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
  }
}

Veo 3.2 Key Differentiators

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

Knowledge Base

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.