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 GoogleCloudPlatform/vertex-ai-samples --skill vertex-inferencegit clone --depth 1 https://github.com/GoogleCloudPlatform/vertex-ai-samplesWrote 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/googlecloudplatform/vertex-ai-samples/vertex-inference)<a href="https://agentmods.dev/skills/googlecloudplatform/vertex-ai-samples/vertex-inference"><img src="https://agentmods.dev/badge/skills/googlecloudplatform/vertex-ai-samples/vertex-inference/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/googlecloudplatform/vertex-ai-samples/vertex-inference"><img src="https://agentmods.dev/badge/skills/googlecloudplatform/vertex-ai-samples/vertex-inference.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 111 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 124 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 123 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00000 | $0.03209 |
| Opus 5.5 | $0.00000 | $0.01284 |
| Sonnet 5.5 | $0.00000 | $0.00642 |
| Haiku 4.5 | $0.00000 | $0.00321 |
Grade A, and why
vertex-inference scanned grade A with 1 finding 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 1mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
> 3. Look for the **"Sample Code"** or **"Use this model"** button on the Model Garden page to get the exact `curl` or Python code for that specific model version. How it starts
The opening of the file, as written. The whole thing — 247 lines — stays where its author put it; the contents beside it link to each section on GitHub.
name: Vertex AI GenAI Inference description: Instructions for connecting to and performing inference with Google Cloud Vertex AI GenAI models, including Gemini and OpenMaaS (Llama, DeepSeek, Qwen, etc.).
Vertex AI GenAI Inference Skill
This skill provides instructions for authenticating and connecting to Google Cloud Vertex AI to use Generative AI models. It covers both First-Party (Gemini) and Third-Party (OpenMaaS) models.
[!TIP] Sample Scripts: This skill includes fully functional sample scripts in the
scripts/directory (e.g.,scripts/openmaas_openai_sdk.py). When running these scripts, ALWAYS create and use a local virtual environment:python3 -m venv .venv && source .venv/bin/activate pip install -r scripts/requirements.txtVerify All Scripts: You can run all scripts at once to verify your setup:
./scripts/verify_all.sh
[!IMPORTANT] CRITICAL: Model IDs & Availability
- Gemini Models: See Gemini Models for valid Model IDs and Regions.
- OpenMaaS Models: See Use Open Models on Vertex AI for Llama, DeepSeek, Qwen, etc.
- Incomplete Lists: The Model IDs listed in this skill are examples only and may be incomplete or outdated.
- Action: Always verify the Model ID and Region using the links above before generating code.
What ships with it
8 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.
- scripts/gemini_genai_sdk.py 1014 B runs code
- scripts/gemini_openai_sdk.py 1.2 KB runs code
- scripts/gemini_vertexai_sdk.py 927 B runs code
- scripts/openmaas_genai_sdk.py 1.1 KB runs code
- scripts/openmaas_openai_sdk.py 1.4 KB runs code
- scripts/openmaas_vertexai_sdk.py 1.0 KB runs code
- scripts/requirements.txt 56 B
- scripts/verify_all.sh 1.5 KB runs code
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.
- 1mo ago First seen · 247 lines · 0 tokens per session scan A 6cba4fa6098e
vertex-inference is a skill published in the GitHub repository GoogleCloudPlatform/vertex-ai-samples (790 stars, last pushed 3d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 3,209 tokens. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
marimo-pair
Drive a live marimo notebook as a workspace: run Python in the same kernel the user does, inspect live notebook state, and commit durable notebook changes. Use when the user wants to start a marimo notebook or pair on an active marimo session.
setup
Configure MLflow tracing for Claude Code.
pyhealth
Comprehensive healthcare AI toolkit for developing, testing, and deploying machine learning models with clinical data. This skill should be used when working with electronic health records (EHR), clinical prediction tasks (mortality, readmission, drug recommendation), medical coding systems (ICD, NDC, ATC)…
deepchem
Molecular ML with diverse featurizers and pre-built datasets. Use for property prediction (ADMET, toxicity) with traditional ML or GNNs when you want extensive featurization options and MoleculeNet benchmarks. Best for quick experiments with pre-trained models, diverse molecular representations. For graph-first…
shap
Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing…
torch-geometric
Graph Neural Networks (PyG). Node/graph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property prediction, for geometric deep learning.