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 agentmods add skills/jpantsjoha/googlecloud-plugin/vertex-ainpx skills add jpantsjoha/googlecloud-plugin --skill vertex-aigit clone --depth 1 https://github.com/jpantsjoha/googlecloud-pluginWrote 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/jpantsjoha/googlecloud-plugin/vertex-ai)<a href="https://agentmods.dev/skills/jpantsjoha/googlecloud-plugin/vertex-ai"><img src="https://agentmods.dev/badge/skills/jpantsjoha/googlecloud-plugin/vertex-ai.svg" alt="Measured on agentmods" 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 | $0.00136 | $0.00876 |
| Opus 5 | $0.00068 | $0.00438 |
| Sonnet 5 | $0.00027 | $0.00175 |
| Haiku 4.5 | $0.00014 | $0.00088 |
Grade A, and why
vertex-ai 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 3d 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.
How it starts
The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Vertex AI
Unified ML platform for training, deploying, and serving models — including Gemini, generative AI, and custom models.
Naming currency: the platform was renamed to the Gemini Enterprise Agent Platform (GEAP) at Next '26 (2026-04-22). The rebrand is branding-only —
vertex-aipersists in gcloud groups, SDK imports, API hostnames, Terraform resources, and doc URLs, so this skill keeps them. For agentic system design (ADK, Agent Runtime, multi-agent, MCP/A2A/AP2, agent evaluation), route toagent-architect; this skill covers platform/model mechanics.
Key Products
| Product | Use |
|---|---|
| Gemini API on Vertex | Production-grade Gemini access with data governance |
| Model Garden | Browse and deploy 150+ models (Gemini, Llama, etc.) |
| Custom Training | Train on managed infrastructure (GPUs/TPUs) |
| Vertex AI Endpoints | Serve predictions from deployed models |
| Agent Builder | Build conversational agents on Vertex |
| Vertex AI Pipelines | Orchestrate ML workflows (Kubeflow Pipelines) |
Core Patterns
Call Gemini via Vertex (Python)
import vertexai
from vertexai.generative_models import GenerativeModel
vertexai.init(project="PROJECT_ID", location="us-central1")
model = GenerativeModel("gemini-2.0-flash-001")
response = model.generate_content("Explain Cloud Run in one sentence.")
print(response.text)
Deploy an endpoint (billable — confirm first)
# Billable: endpoints charge per node-hour when deployed
gcloud ai endpoints create \
--display-name=ENDPOINT_NAME \
--region=REGION \
--project=PROJECT_ID
Grant Vertex AI access (least-privilege)
gcloud projects add-iam-policy-binding PROJECT_ID \
--member="serviceAccount:[email protected]" \
--role="roles/aiplatform.user"
Safety Rules
- Endpoints incur cost even when idle — undeploy when not needed
- Use
roles/aiplatform.userfor inference;roles/aiplatform.adminonly for platform admins - Cost warning: GPUs and TPUs are expensive — confirm instance type and count before training
What ships with it
1 file 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.
- 3d ago First seen · 73 lines · 136 tokens per session scan A ded0836742ce
vertex-ai is a skill published in the GitHub repository jpantsjoha/googlecloud-plugin (4 stars, last pushed 27d ago), licensed MIT. It adds 136 tokens to every session and 876 once invoked, about $0.0007 per session on Opus 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 2026-08-31.
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