developing-genkit-dart

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Generates code and provides documentation for the Genkit Dart SDK. Use when the user asks to build AI agents in Dart, use Genkit flows, or integrate LLMs into Dart/Flutter applications.

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Sourcegenkit-ai/skills
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NPX Install

npx skill4agent add genkit-ai/skills developing-genkit-dart

SKILL.md Content

Genkit Dart

Genkit Dart is an AI SDK for Dart that provides a unified interface for code generation, structured outputs, tools, flows, and AI agents.

Core Features and Usage

If you need help with initializing Genkit (
Genkit()
), Generation (
ai.generate
), Tooling (
ai.defineTool
), Flows (
ai.defineFlow
), Embeddings (
ai.embedMany
), streaming, or calling remote flow endpoints, please load the core framework reference: references/genkit.md

Genkit CLI (recommended)

The Genkit CLI provides a local development UI for running Flow, tracing executions, playing with models, and evaluating outputs.
check if the user has it installed: 
genkit --version
Installation:
bash
curl -sL cli.genkit.dev | bash # Native CLI
# OR
npm install -g genkit-cli # Via npm
Usage: Wrap your run command with 
genkit start
to attach the Genkit developer UI and tracing:
bash
genkit start -- dart run main.dart

Plugin Ecosystem

Genkit relies on a large suite of plugins to perform generative AI actions, interface with external LLMs, or host web servers.
When asked to use any given plugin, always verify usage by referring to its corresponding reference below. You should load the reference when you need to know the specific initialization arguments, tools, models, and usage patterns for the plugin:
Plugin NameReference LinkDescription
genkit_google_genai
references/genkit_google_genai.mdLoad for Google Gemini plugin interface usage.
genkit_anthropic
references/genkit_anthropic.mdLoad for Anthropic plugin interface for Claude models.
genkit_openai
references/genkit_openai.mdLoad for OpenAI plugin interface for GPT models, Groq, and custom compatible endpoints.
genkit_middleware
references/genkit_middleware.mdLoad for Tooling for specific agentic behavior: 
filesystem
, 
skills
, and 
toolApproval
interrupts.
genkit_mcp
references/genkit_mcp.mdLoad for Model Context Protocol integration (Server, Host, and Client capabilities).
genkit_chrome
references/genkit_chrome.mdLoad for Running Gemini Nano locally inside the Chrome browser using the Prompt API.
genkit_shelf
references/genkit_shelf.mdLoad for Integrating Genkit Flow actions over HTTP using Dart Shelf.
genkit_firebase_ai
references/genkit_firebase_ai.mdLoad for Firebase AI plugin interface (Gemini API via Vertex AI).

External Dependencies

Whenever you define schemas mapping inside of Tools, Flows, and Prompts, you must use the schemantic library. To learn how to use schemantic, ensure you read references/schemantic.md for how to implement type safe generated Dart code. This is particularly relevant when you encounter symbols like 
@Schema()
, 
SchemanticType
, or classes with the 
$
prefix. Genkit Dart uses schemantic for all of its data models so it's a CRITICAL skill to understand for using Genkit Dart.

Best Practices

  • Always check that code cleanly compiles using 
    dart analyze
    before generating the final response.
  • Always use the Genkit CLI for local development and debugging.