genkit-ai

TypeScript coding conventions, best practices, and patterns for writing clean, maintainable code.

Conventions for clean, idiomatic Python. Load whenever you read, edit, or write Python source files.

How to write pytest tests for modules in this workspace. Load whenever you are about to write or extend tests.

Explain concepts in very simple terms suitable for a five-year-old.

Respond as a single traditional haiku with a 5-7-5 syllable structure.

Respond in the voice of a swashbuckling pirate.

Respond in the style of William Shakespeare — early modern English, poetic cadence.

A skill for coding that should apply to all coding tasks.

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.

Develop AI-powered applications using Genkit in Go. Use when the user asks to build AI features, agents, flows, or tools in Go using Genkit, or when working with Genkit Go code involving generation, prompts, streaming, tool calling, or model providers.

Develop AI-powered applications using Genkit in Node.js/TypeScript. Use when the user asks about Genkit, AI agents, flows, or tools in JavaScript/TypeScript, or when encountering Genkit errors, validation issues, type errors, or API problems.

Develop AI-powered applications using Genkit in Python. Use when the user asks about Genkit, AI agents, flows, or tools in Python, or when encountering Genkit errors, import issues, or API problems.

Guide for building AI-powered Java applications using the Genkit Java framework. Use this skill when the user wants to create a new AI app, add AI features to an existing Java project, define flows, call models, use tools, build RAG pipelines, manage prompts, handle structured output, set up multi-turn chat, create agents, run evaluations, or deploy with Genkit Java. Covers all supported providers (OpenAI, Google Gemini, Anthropic, Ollama, AWS Bedrock, Azure, and more).

Best practices for developing with and contributing to Genkit Java — the open-source Java AI framework by Google. Covers project architecture, plugin development, flow definition, model integration, RAG pipelines, testing, naming conventions, and code quality guidelines. Use this skill when the user asks about building AI applications in Java with Genkit, creating custom plugins, defining flows, working with models, embedders, retrievers, tools, prompts, agents, or contributing to the Genkit Java codebase.

Conventions and best practices for writing Dart code in this workspace.