npx claudepluginhub firebase/agent-skills --plugin firebaseThis skill uses the workspace's default tool permissions.
Genkit Dart is an AI SDK for Dart that provides a unified interface for code generation, structured outputs, tools, flows, and AI agents.
Generates design tokens/docs from CSS/Tailwind/styled-components codebases, audits visual consistency across 10 dimensions, detects AI slop in UI.
Records polished WebM UI demo videos of web apps using Playwright with cursor overlay, natural pacing, and three-phase scripting. Activates for demo, walkthrough, screen recording, or tutorial requests.
Delivers idiomatic Kotlin patterns for null safety, immutability, sealed classes, coroutines, Flows, extensions, DSL builders, and Gradle DSL. Use when writing, reviewing, refactoring, or designing Kotlin code.
Genkit Dart is an AI SDK for Dart that provides a unified interface for code generation, structured outputs, tools, flows, and AI agents.
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
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
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 Name | Reference Link | Description |
|---|---|---|
genkit_google_genai | references/genkit_google_genai.md | Load for Google Gemini plugin interface usage. |
genkit_anthropic | references/genkit_anthropic.md | Load for Anthropic plugin interface for Claude models. |
genkit_openai | references/genkit_openai.md | Load for OpenAI plugin interface for GPT models, Groq, and custom compatible endpoints. |
genkit_middleware | references/genkit_middleware.md | Load for Tooling for specific agentic behavior: filesystem, skills, and toolApproval interrupts. |
genkit_mcp | references/genkit_mcp.md | Load for Model Context Protocol integration (Server, Host, and Client capabilities). |
genkit_chrome | references/genkit_chrome.md | Load for Running Gemini Nano locally inside the Chrome browser using the Prompt API. |
genkit_shelf | references/genkit_shelf.md | Load for Integrating Genkit Flow actions over HTTP using Dart Shelf. |
genkit_firebase_ai | references/genkit_firebase_ai.md | Load for Firebase AI plugin interface (Gemini API via Vertex AI). |
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.
dart analyze before generating the final response.