Developing Genkit Go
Skill Verified ActiveDevelop 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.
To enable developers to build AI-powered applications, agents, and tools efficiently using the Genkit SDK in Go, providing structure and best practices.
Features
- Genkit SDK initialization and configuration in Go
- Defining and executing text, data, and streaming generation
- Creating and using prompts, including typed and file-based prompts
- Integrating tools with interrupt and response handling
- Building and deploying AI flows via HTTP handlers
Use Cases
- When a user asks to build AI features, agents, or flows in Go using Genkit.
- When working with Genkit Go code involving generation, prompts, streaming, or tool calling.
- When setting up model providers like Google AI, Anthropic, or OpenAI-compatible APIs within a Go application.
- When developing structured AI outputs or complex AI logic via Genkit flows.
Non-Goals
- Providing specific AI models; relies on Genkit's provider integrations.
- Managing deployment infrastructure for Genkit applications.
- Replacing the core Genkit SDK or Go language itself.
Workflow
- Initialize Genkit with plugins and configuration.
- Define AI resources like prompts, tools, and flows.
- Integrate AI logic into Go application code.
- Optionally, expose flows as HTTP endpoints.
- Utilize the Genkit CLI for development and tracing.
Practices
- AI Development
- Go Programming
- SDK Usage
- Prompt Engineering
Prerequisites
- Go programming language environment
- Genkit SDK for Go
- Access to configured AI model providers (e.g., API keys)
Installation
First, add the marketplace
/plugin marketplace add firebase/agent-skills/plugin install agent-skills@firebaseQuality Score
VerifiedTrust Signals
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