Genkit Dart

SkillAI & models

Once added, your AI can build and manage Firebase apps written in Dart. It knows how to work with Genkit, so it can write and update the Dart code your Firebase projects need.

Available today. Use it from your connected AI after setup.

Add the skill, then ask your AI to build a Firebase app in Dart or update one you already have. You can also ask it to set up Genkit in an existing Dart project.

Then ask your AI: use the Genkit Dart skill

What your AI can do with it

  • Build Firebase apps in Dart
  • Manage Firebase apps on your behalf
  • Write and update Dart code that uses Genkit
  • Set up Genkit in a new or existing Dart project
  • Take on Firebase development tasks in Dart for you

What this skill tells your AI

The instructions your AI receives, as published by evanca/flutter-ai-rules in skills/developing-genkit-dart/SKILL.md and read by ahel’s review.

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:

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:

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_genaireferences/genkit_google_genai.mdLoad for Google Gemini plugin interface usage.
genkit_anthropicreferences/genkit_anthropic.mdLoad for Anthropic plugin interface for Claude models.
genkit_openaireferences/genkit_openai.mdLoad for OpenAI plugin interface for GPT models, Groq, and custom compatible endpoints.
genkit_middlewarereferences/genkit_middleware.mdLoad for Tooling for specific agentic behavior: filesystem, skills, and toolApproval interrupts.
genkit_mcpreferences/genkit_mcp.mdLoad for Model Context Protocol integration (Server, Host, and Client capabilities).
genkit_chromereferences/genkit_chrome.mdLoad for Running Gemini Nano locally inside the Chrome browser using the Prompt API.
genkit_shelfreferences/genkit_shelf.mdLoad for Integrating Genkit Flow actions over HTTP using Dart Shelf.
genkit_firebase_aireferences/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.

Signals

GitHub stars
637
Forks
66
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
developing-genkit-dart
Source
github.com/evanca/flutter-ai-rules