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 genai-sdkgit 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/genai-sdk)<a href="https://agentmods.dev/skills/googlecloudplatform/vertex-ai-samples/genai-sdk"><img src="https://agentmods.dev/badge/skills/googlecloudplatform/vertex-ai-samples/genai-sdk/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/genai-sdk"><img src="https://agentmods.dev/badge/skills/googlecloudplatform/vertex-ai-samples/genai-sdk.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00073 | $0.02240 |
| Opus 5.5 | $0.00029 | $0.00896 |
| Sonnet 5.5 | $0.00015 | $0.00448 |
| Haiku 4.5 | $0.00007 | $0.00224 |
Grade A, and why
genai-sdk 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 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.
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 — 226 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Gemini API in Vertex AI
Access Google's most advanced AI models built for enterprise use cases using the Gemini API in Vertex AI.
Provide these key capabilities:
- Text generation - Chat, completion, summarization
- Multimodal understanding - Process images, audio, video, and documents
- Function calling - Let the model invoke your functions
- Structured output - Generate valid JSON matching your schema
- Context caching - Cache large contexts for efficiency
- Embeddings - Generate text embeddings for semantic search
- Live Realtime API - Bidirectional streaming for low latency Voice and Video interactions
- Batch Prediction - Handle massive async dataset prediction workloads
Core Directives
- Unified SDK: ALWAYS use the Gen AI SDK (
google-genaifor Python,@google/genaifor JS/TS,google.golang.org/genaifor Go,com.google.genai:google-genaifor Java,Google.GenAIfor C#). - Legacy SDKs: DO NOT use
google-cloud-aiplatform,@google-cloud/vertexai, orgoogle-generativeai.
SDKs
- Python: Install
google-genaiwithpip install google-genai - JavaScript/TypeScript: Install
@google/genaiwithnpm install @google/genai - Go: Install
google.golang.org/genaiwithgo get google.golang.org/genai - C#/.NET: Install
Google.GenAIwithdotnet add package Google.GenAI - Java:
-
groupId:
com.google.genai, artifactId:google-genai -
Latest version can be found here: https://central.sonatype.com/artifact/com.google.genai/google-genai/versions (let's call it
LAST_VERSION) -
Install in
build.gradle:implementation("com.google.genai:google-genai:${LAST_VERSION}") -
Install Maven dependency in
pom.xml:<dependency> <groupId>com.google.genai</groupId> <artifactId>google-genai</artifactId> <version>${LAST_VERSION}</version> </dependency>
-
[!WARNING] Legacy SDKs like
google-cloud-aiplatform,@google-cloud/vertexai, andgoogle-generativeaiare deprecated. Migrate to the new SDKs above urgently by following the Migration Guide.
What ships with it
13 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.
- references/advanced_features.md 4.4 KB
- references/bounding_box.md 1.8 KB
- references/embeddings.md 590 B
- references/live_api/live_api.md 1.0 KB
- references/live_api/references/client_server_messages.md 33 KB
- references/live_api/references/client_server_messages.proto 12 KB
- references/live_api/references/session_manager.md 4.4 KB
- references/live_api/SKILL.md 4.8 KB
- references/media_generation.md 3.0 KB
- references/model_tuning.md 934 B
- references/safety.md 1.8 KB
- references/structured_and_tools.md 3.7 KB
- references/text_and_multimodal.md 2.3 KB
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 · 226 lines · 73 tokens per session scan A 9ee27b105f06
genai-sdk is a skill published in the GitHub repository GoogleCloudPlatform/vertex-ai-samples (791 stars, last pushed 3d ago), licensed Apache-2.0. It adds 73 tokens to every session and 2,240 once invoked, about $0.0003 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.
Other skills, from other repositories
cortex-integrate
Design and implement an AI feature integration — model selection, architecture pattern, system prompt, data flow, error handling, cost estimate. Use when asked to "add AI to this", "LLM integration", "add Claude/GPT", or "AI-powered feature".
Forsion Connect AI SDK
Build web pages/apps that call Forsion's AI (LLM chat, server-managed agent conversations with web search, image generation) using the signed-in Forsion account — one script tag, no API keys. Use this whenever the user wants a website or HTML page with any AI feature (smart import/parsing, chatbot/assistant, AI…
add-llm-fallbacks
Use this to make an LLM app resilient to provider failures, rate limits, timeouts, and outages. Trigger on "handle LLM API errors", "add retries/fallbacks", "the app breaks when OpenAI is down", "rate limit errors", "make my LLM calls reliable", "timeout handling". Add retries, timeouts, and model/provider fallbacks…
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.
gemini-api-agent-platform
Guides the usage of the Gemini API on Agent Platform with the Google Gen AI SDK for enterprise AI applications. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like Live API, tools, multimedia generation, caching, and batch prediction.
open-source
Documentation reference for writing Python code using the browser-use open-source library. Use this skill whenever the user needs help with Agent, Browser, or Tools configuration, is writing code that imports from browseruse, asks about @sandbox deployment, supported LLM models, Actor API, custom tools, lifecycle…