/gemini-api
Use when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI, Google Cloud, or Agent Platform. Guides the usage of the Gemini API on Agent Platform with the Google Gen AI SDK. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities
Claude Code
$ npx -y skills add google/skills --skill gemini-api --agent claude-code
Codex
$ npx skills add google/skills --skill gemini-api -a codex -y
Cursor
$ npx skills add google/skills --skill gemini-api -a cursor -y
Gemini CLI
$ npx skills add google/skills --skill gemini-api -a gemini-cli -y
GitHub Copilot
$ npx skills add google/skills --skill gemini-api -a github-copilot -y
OpenCode
$ npx skills add google/skills --skill gemini-api -a opencode -y
Windsurf
$ npx skills add google/skills --skill gemini-api -a windsurf -y
SKILL.md
gemini-api.SKILL.mdname: gemini-api
metadata:
version: "1.0.2"
category: AiAndMachineLearning
description: Use when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI, Google Cloud, or Agent Platform. Guides the usage of the Gemini API on Agent Platform with the Google Gen AI SDK. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like multimodal inputs, tools, media generation, caching, batch prediction, and Live API.
compatibility: Requires active Google Cloud credentials and Agent Platform API enabled.
> [!IMPORTANT] > Agent Platform (full name Gemini Enterprise Agent Platform) was previously named "Vertex AI" and many web resources use the legacy branding.
Gemini API in Agent Platform
Access Google's most advanced AI models built for enterprise use cases using the Gemini API in Agent Platform.
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
Attribution
**MUST READ**: Before executing any `gcloud`, REST API, or MCP command, you MUST read [Usage Attribution](references/attribution.md). For commands executed directly in the terminal (never in generated scripts, Terraform, or user code), prefix `gcloud` with `CLOUDSDK_METRICS_REQUEST_ATTRIBUTION="agent-skills/1.0 (skill:gemini-api)"` and append `agent-skills/1.0 (skill:gemini-api)` to `User-Agent` headers.
Core Directives
- **Unified SDK**: ALWAYS use the Gen AI SDK (`google-genai` for Python, `@google/genai` for JS/TS, `google.golang.org/genai` for Go, `com.google.genai:google-genai` for Java, `Google.GenAI` for C#).
- **Legacy SDKs**: DO NOT use `google-cloud-aiplatform`, `@google-cloud/vertexai`, or `google-generativeai`.
SDKs
- **Python**: Install `google-genai` with `pip install google-genai`
- **JavaScript/TypeScript**: Install `@google/genai` with `npm install @google/genai`
- **Go**: Install `google.golang.org/genai` with `go get google.golang.org/genai`
- **C#/.NET**: Install `Google.GenAI` with `dotnet 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`, and `google-generativeai` are deprecated. Migrate to the new SDKs above urgently by following the [Migration Guide](https://docs.cloud.google.com/vertex-ai/generative-ai/docs/deprecations/genai-vertexai-sdk.md.txt).
Authentication & Configuration
Prefer environment variables over hard-coding parameters when creating the client. Initialize the client without parameters to automatically pick up these values.
Application Default Credentials (ADC)
Set these variables for standard [Google Cloud authentication](https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/start/gcp-auth.md.txt):
export GOOGLE_CLOUD_PROJECT='your-project-id'
# Note: global location is supported for standard inference; regional endpoint (e.g. us-central1) required for Live API
export GOOGLE_CLOUD_LOCATION='global'
export GOOGLE_GENAI_USE_ENTERPRISE=true
- By default, use `location="global"` to access the global endpoint, which provides automatic routing to regions with available capacity.
- If a user explicitly asks to use a specific region (e.g., `us-central1`, `europe-west4`), specify that region in the `GOOGLE_CLOUD_LOCATION` parameter instead. Reference the [supported regions documentation](https://docs.cloud.google.com/gemini-enterprise-agent-platform/resources/locations.md.txt) if needed.
Agent Platform in Express Mode
Set these variables when using [Express Mode](https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/start/api-keys.md.txt) with an API key:
export GOOGLE_API_KEY='your-api-key'
export GOOGLE_GENAI_USE_ENTERPRISE=true
Initialization
Initialize the client without arguments to pick up environment variables:
from google import genai
client = genai.Client()
Alternatively, you can hard-code in parameters when creating the client.
from google import genai
client = genai.Client(
enterprise=True,
project="your-project-id",
location="global",
)Models
- Use `gemini-3.8-flash` for fast, balanced performance, multimodal (1M tokens)
- Use `gemini-3.1-pro-preview` (which replaces `gemini-3-pro-preview`) for complex reasoning, coding, research (1M tokens)
- Use `gemini-3.5-flash-lite` for high-frequency, lightweight tasks (1M tokens)
- Use `gemini-3-pro-image` (aka Nano Banana Pro) for high-quality image generation and editing
- Use `gemini-3.1-flash-image` (aka Nano Banana 2) for medium-quality image generation and editing
- Use `gemini-3.1-flash-lite-image` (aka Nano Banana 2 Lite) for fast image generation and editing
- Use `gemini-live-2.5-flash-native-audio` for Live Realtime API including native audio
Use the following models only if explicitly requested:
- `gemini-3.7-flash`
- `gemini-3.6-flash`
- `gemini-3.5-flash`
- `gemini-3.1-flash-lite`
- `gemini-2.5-flash-image`
- `
Read more
name: gemini-api metadata: version: "1.0.2" category: AiAndMachineLearning description: Use when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI, Google Cloud, or Agent Platform. Guides the usage of the Gemini API on Agent Platform with the Google Gen AI SDK. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like multimodal inputs, tools, media generation, caching, batch prediction, and Live API. compatibility: Requires active Google Cloud credentials and Agent Platform API enabled.
> [!IMPORTANT] > Agent Platform (full name Gemini Enterprise Agent Platform) was previously named "Vertex AI" and many web resources use the legacy branding.
Gemini API in Agent Platform
Access Google's most advanced AI models built for enterprise use cases using the Gemini API in Agent Platform.
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
Attribution
**MUST READ**: Before executing any `gcloud`, REST API, or MCP command, you MUST read [Usage Attribution](references/attribution.md). For commands executed directly in the terminal (never in generated scripts, Terraform, or user code), prefix `gcloud` with `CLOUDSDK_METRICS_REQUEST_ATTRIBUTION="agent-skills/1.0 (skill:gemini-api)"` and append `agent-skills/1.0 (skill:gemini-api)` to `User-Agent` headers.
Core Directives
- **Unified SDK**: ALWAYS use the Gen AI SDK (`google-genai` for Python, `@google/genai` for JS/TS, `google.golang.org/genai` for Go, `com.google.genai:google-genai` for Java, `Google.GenAI` for C#).
- **Legacy SDKs**: DO NOT use `google-cloud-aiplatform`, `@google-cloud/vertexai`, or `google-generativeai`.
SDKs
- **Python**: Install `google-genai` with `pip install google-genai`
- **JavaScript/TypeScript**: Install `@google/genai` with `npm install @google/genai`
- **Go**: Install `google.golang.org/genai` with `go get google.golang.org/genai`
- **C#/.NET**: Install `Google.GenAI` with `dotnet 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`, and `google-generativeai` are deprecated. Migrate to the new SDKs above urgently by following the [Migration Guide](https://docs.cloud.google.com/vertex-ai/generative-ai/docs/deprecations/genai-vertexai-sdk.md.txt).
Authentication & Configuration
Prefer environment variables over hard-coding parameters when creating the client. Initialize the client without parameters to automatically pick up these values.
Application Default Credentials (ADC)
Set these variables for standard [Google Cloud authentication](https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/start/gcp-auth.md.txt):
export GOOGLE_CLOUD_PROJECT='your-project-id' # Note: global location is supported for standard inference; regional endpoint (e.g. us-central1) required for Live API export GOOGLE_CLOUD_LOCATION='global' export GOOGLE_GENAI_USE_ENTERPRISE=true
- By default, use `location="global"` to access the global endpoint, which provides automatic routing to regions with available capacity.
- If a user explicitly asks to use a specific region (e.g., `us-central1`, `europe-west4`), specify that region in the `GOOGLE_CLOUD_LOCATION` parameter instead. Reference the [supported regions documentation](https://docs.cloud.google.com/gemini-enterprise-agent-platform/resources/locations.md.txt) if needed.
Agent Platform in Express Mode
Set these variables when using [Express Mode](https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/start/api-keys.md.txt) with an API key:
export GOOGLE_API_KEY='your-api-key' export GOOGLE_GENAI_USE_ENTERPRISE=true
Initialization
Initialize the client without arguments to pick up environment variables:
from google import genai client = genai.Client()
Alternatively, you can hard-code in parameters when creating the client.
from google import genai
client = genai.Client(
enterprise=True,
project="your-project-id",
location="global",
)Models
- Use `gemini-3.8-flash` for fast, balanced performance, multimodal (1M tokens)
- Use `gemini-3.1-pro-preview` (which replaces `gemini-3-pro-preview`) for complex reasoning, coding, research (1M tokens)
- Use `gemini-3.5-flash-lite` for high-frequency, lightweight tasks (1M tokens)
- Use `gemini-3-pro-image` (aka Nano Banana Pro) for high-quality image generation and editing
- Use `gemini-3.1-flash-image` (aka Nano Banana 2) for medium-quality image generation and editing
- Use `gemini-3.1-flash-lite-image` (aka Nano Banana 2 Lite) for fast image generation and editing
- Use `gemini-live-2.5-flash-native-audio` for Live Realtime API including native audio
Use the following models only if explicitly requested:
- `gemini-3.7-flash`
- `gemini-3.6-flash`
- `gemini-3.5-flash`
- `gemini-3.1-flash-lite`
- `gemini-2.5-flash-image`
- `
This repository contains Agent Skills for Google products and technologies, including Google Cloud.
Other skills on skills.
More skills from other plugins.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, modifying behavior, or…
ask-matt
Ask which skill or flow fits your situation. A router over the skills in this repo.
Questions about gemini-api.
- Which coding agents can use gemini-api?
- gemini-api installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.

