Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add cnemri/google-genai-skills --skill veo-buildgit clone --depth 1 https://github.com/cnemri/google-genai-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/cnemri/google-genai-skills/veo-build)<a href="https://agentmods.dev/skills/cnemri/google-genai-skills/veo-build"><img src="https://agentmods.dev/badge/skills/cnemri/google-genai-skills/veo-build/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/cnemri/google-genai-skills/veo-build"><img src="https://agentmods.dev/badge/skills/cnemri/google-genai-skills/veo-build.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00039 | $0.00496 |
| Opus 5.5 | $0.00016 | $0.00198 |
| Sonnet 5.5 | $0.00008 | $0.00099 |
| Haiku 4.5 | $0.00004 | $0.00050 |
Grade A, and why
veo-build scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Veo Video Generation and Editing
This skill provides comprehensive workflows for using Google's Veo models (Veo 2 and Veo 3) via the google-genai Python SDK.
Quick Start Setup
All Veo operations require the google-genai library and an authenticated client with Vertex AI enabled.
from google import genai
from google.genai import types
import os
PROJECT_ID = os.environ.get("GOOGLE_CLOUD_PROJECT")
LOCATION = os.environ.get("GOOGLE_CLOUD_REGION", "us-central1")
client = genai.Client(vertexai=True, project=PROJECT_ID, location=LOCATION)
Reference Materials
- Generation (Veo 3): Text-to-Video, Image-to-Video.
- Editing (Veo 2): Inpainting, Masking.
- Advanced Controls: Frame Interpolation, Video Extension, Reference Images.
- Prompting Guide: Camera angles, visual styles, and best practices.
- Source Code: Deep inspection of SDK internals (
models.py,types.py).
Available Workflows
1. Video Generation (Veo 3)
Create new videos from text or image prompts.
- Text-to-Video: Create videos from detailed text descriptions.
- Image-to-Video: Animate static images.
- Prompt Engineering: Optimization keywords for camera, lighting, and style.
2. Video Editing (Veo 2)
Modify existing videos using masks (Inpainting).
- Remove Objects: Erase dynamic or static objects.
- Insert Objects: Add new elements into a scene.
3. Advanced Controls (Veo 3)
Specialized generation tasks for precise control.
- Frame Interpolation: Generate video bridging two images (first & last frame).
- Video Extension: Extend the duration of an existing video clip.
- Reference-to-Video: Use specific asset images (subjects, products) to guide generation.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 50 lines · 39 tokens per session scan A 22e6e670c8e1
veo-build is a skill published in the GitHub repository cnemri/google-genai-skills (129 stars, last pushed 9mo ago), licensed MIT. It adds 39 tokens to every session and 496 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
veo-build compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| veo-buildcnemri/google-genai-skills | Skill | 129 | 9mo ago | MIT | A | 39 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |