3.6k★by okaris
google-veo – OpenClaw Skill
google-veo is an OpenClaw Skills integration for data analytics workflows. |
Skill Snapshot
| name | google-veo |
| description | | OpenClaw Skills integration. |
| owner | okaris |
| repository | okaris/inference-shpath: google-veo |
| language | Markdown |
| license | MIT |
| topics | |
| security | L1 |
| install | openclaw add @okaris/inference-sh:google-veo |
| last updated | Feb 7, 2026 |
Maintainer

name: google-veo description: | Generate videos with Google Veo models via inference.sh CLI. Models: Veo 3.1, Veo 3.1 Fast, Veo 3, Veo 3 Fast, Veo 2. Capabilities: text-to-video, cinematic output, high quality video generation. Triggers: veo, google veo, veo 3, veo 2, veo 3.1, vertex ai video, google video generation, google video ai, veo model, veo video allowed-tools: Bash(infsh *)
Google Veo Video Generation
Generate videos with Google Veo models via inference.sh CLI.
Quick Start
curl -fsSL https://cli.inference.sh | sh && infsh login
infsh app run google/veo-3-1-fast --input '{"prompt": "drone shot over a mountain lake"}'
Veo Models
| Model | App ID | Speed | Quality |
|---|---|---|---|
| Veo 3.1 | google/veo-3-1 | Slower | Best |
| Veo 3.1 Fast | google/veo-3-1-fast | Fast | Excellent |
| Veo 3 | google/veo-3 | Medium | Excellent |
| Veo 3 Fast | google/veo-3-fast | Fast | Very Good |
| Veo 2 | google/veo-2 | Medium | Good |
Search Veo Apps
infsh app list --search "veo"
Examples
Cinematic Shot
infsh app run google/veo-3-1-fast --input '{
"prompt": "Cinematic drone shot flying through a misty forest at sunrise, volumetric lighting"
}'
Product Demo
infsh app run google/veo-3 --input '{
"prompt": "Sleek smartphone rotating on a dark reflective surface, studio lighting"
}'
Nature Scene
infsh app run google/veo-3-1-fast --input '{
"prompt": "Timelapse of clouds moving over a mountain range, golden hour"
}'
Action Shot
infsh app run google/veo-3 --input '{
"prompt": "Slow motion water droplet splashing into a pool, macro shot"
}'
Urban Scene
infsh app run google/veo-3-1-fast --input '{
"prompt": "Busy city street at night with neon signs and rain reflections, Tokyo style"
}'
Prompt Tips
Camera movements: drone shot, tracking shot, pan, zoom, dolly, steadicam
Lighting: golden hour, blue hour, studio lighting, volumetric, neon, natural
Style: cinematic, documentary, commercial, artistic, realistic
Timing: slow motion, timelapse, real-time
Sample Workflow
# 1. Generate sample input to see all options
infsh app sample google/veo-3-1-fast --save input.json
# 2. Edit the prompt
# 3. Run
infsh app run google/veo-3-1-fast --input input.json
Related Skills
# Full platform skill (all 100+ apps)
npx skills add inference-sh/skills@inference-sh
# All video generation models
npx skills add inference-sh/skills@ai-video-generation
# AI avatars & lipsync
npx skills add inference-sh/skills@ai-avatar-video
# Image generation (for image-to-video)
npx skills add inference-sh/skills@ai-image-generation
Browse all video apps: infsh app list --category video
No README available.
Permissions & Security
Security level L1: Low-risk skills with minimal permissions. Review inputs and outputs before running in production.
Requirements
- OpenClaw CLI installed and configured.
- Language: Markdown
- License: MIT
- Topics:
FAQ
How do I install google-veo?
Run openclaw add @okaris/inference-sh:google-veo in your terminal. This installs google-veo into your OpenClaw Skills catalog.
Does this skill run locally or in the cloud?
OpenClaw Skills execute locally by default. Review the SKILL.md and permissions before running any skill.
Where can I verify the source code?
The source repository is available at https://github.com/openclaw/skills/tree/main/skills/okaris/inference-sh. Review commits and README documentation before installing.
