Agent skill · software engineering · aiskillstore
genkit
Build production-ready AI workflows using Firebase Genkit. Use when creating flows, tool-calling agents, RAG pipelines, multi-agent systems, or deploying AI to Firebase/Cloud Run. Supports TypeScript, Go, and Python with Gemini, OpenAI, Anthropic, Ollama, and Vertex AI plugins.
Why this skill is useful
Adds executable scripts and workflows for building production-ready AI pipelines using Firebase Genkit, which are not commonly found in public documentation.
What it needs
Requires genkit-cli installed locally. Requires anthropic, google-cloud, openai account access. About 9k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
Firebase Genkit When to use this skill AI workflow orchestration: Building multi-step AI pipelines with type-safe inputs/outputs Flow-based APIs: Wrapping LLM calls into deployable HTTP endpoints Tool calling / agents: Equipping models with custom tools and implementing agentic loops RAG pipelines: Retrieval-augmented generation with vector databases (Pinecone, pgvector, Firestore, Chroma, etc.) Multi-agent systems: Coordinating multiple specialized AI agents Streaming responses: Real-time token-by-token output for chat or long-form content Firebase/Cloud Run deployment: Deploying AI functions to Google Cloud Prompt management: Managing prompts as versioned .prompt files with Dotprompt --- Installation & Setup Step 1: Install the Genkit CLI Step 2: Create a TypeScript project Step 3: Install Genkit core and a model plugin Step 4: Configure API Key --- Core Concepts Initializing Genkit Defining Flows Flows are the core primitive: type-safe, observable, deployable AI functions. Generating Content Streaming Flows Tool Calling (Agents) Prompts with Dotprompt Manage prompts as versioned .prompt files: RAG — Retrieval-Augmented Generation Chat Sessions Multi-Agent Systems --- Developer Tools CLI Commands Developer UI The Developer UI runs at http://localhost:4000 and provides: Flow runner: Execute flows with custom JSON inputs Trace inspector: Visualize each step (generate, embed, retrieve, tool calls) Prompt playground: Test prompts interactively Model tester: Compare outputs across different models Evaluator: Run evaluation datasets against flows --- Deployment Firebase Cloud Functions Express.js Server Cloud Run --- Supported Plugins Model Providers Plugin Package Models -------- --------- -------- Google AI @genkit-ai/google-genai Gemini 2.5 Flash/Pro Vertex AI @genkit-ai/vertexai Gemini, Imagen, Claude OpenAI genkitx-openai GPT-4o, o1, etc. Anthropic genkitx-anthropic Claude 3.5/3 AWS Bedrock genkitx-aws-bedrock Claude, Titan, etc. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/genkit