developing-genkit-go
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.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/firebase/agent-skills --skill developing-genkit-go- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads developing-genkit-go automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
Security audits
Independent scans of the skill's instructions and bundled files.
SKILL.md
The instructions your agent reads when the skill is triggered.
Genkit Go
Genkit Go is an AI SDK for Go that provides generation, structured output, streaming, tool calling, prompts, and flows with a unified interface across model providers.
Hello World
package main
import (
"context"
"fmt"
"log"
"net/http"
"github.com/genkit-ai/genkit/go/ai"
"github.com/genkit-ai/genkit/go/genkit"
"github.com/genkit-ai/genkit/go/plugins/googlegenai"
"github.com/genkit-ai/genkit/go/plugins/server"
)
func main() {
ctx := context.Background()
g := genkit.Init(ctx, genkit.WithPlugins(&googlegenai.GoogleAI{}))
genkit.DefineFlow(g, "jokeFlow", func(ctx context.Context, topic string) (string, error) {
return genkit.GenerateText(ctx, g,
ai.WithModelName("googleai/gemini-flash-latest"),
ai.WithPrompt("Tell me a joke about %s", topic),
)
})
mux := http.NewServeMux()
for _, f := range genkit.ListFlows(g) {
mux.HandleFunc("POST /"+f.Name(), genkit.Handler(f))
}
log.Fatal(server.Start(ctx, "127.0.0.1:8080", mux))
}
Core Features
Load the appropriate reference based on what you need:
| Feature | Reference | When to load |
|---|---|---|
| Initialization | references/getting-started.md | Setting up genkit.Init, plugins, the *Genkit instance pattern |
| Generation | references/generation.md | Generate, GenerateText, GenerateData, streaming, output formats |
| Prompts | references/prompts.md | DefinePrompt, DefineDataPrompt, .prompt files, schemas |
| Tools | references/tools.md | DefineTool, tool interrupts, RestartWith/RespondWith |
| Middleware | references/middleware.md | ai.Middleware, ai.WithUse, Hooks (Generate/Model/Tool), built-ins (Retry, Fallback, ToolApproval, Filesystem, Skills) |
| Flows & HTTP | references/flows-and-http.md | DefineFlow, DefineStreamingFlow, genkit.Handler, HTTP serving |
| Model Providers | references/providers.md | Google AI, Vertex AI, Anthropic, OpenAI-compatible, Ollama setup |
Genkit CLI
Check if installed: genkit --version
Installation:
curl -sL cli.genkit.dev | bash
Key commands:
# Start app with Developer UI (tracing, flow testing) at http://localhost:4000
genkit start -- go run .
genkit start -o -- go run . # also opens browser
# Run a flow directly from the CLI
genkit flow:run myFlow '{"data": "input"}'
genkit flow:run myFlow '{"data": "input"}' --stream # with streaming
genkit flow:run myFlow '{"data": "input"}' --wait # wait for completion
# Look up Genkit documentation
genkit docs:search "streaming" go
genkit docs:list go
genkit docs:read go/flows.md
See references/getting-started.md for full CLI and Developer UI details.
Key Guidance
- Pass
gexplicitly. The*Genkitinstance returned bygenkit.Initis the central registry. Pass it to all Genkit functions rather than storing it as a global. This is a core pattern throughout the SDK. - Wrap AI logic in flows. Flows give you tracing, observability, HTTP deployment via
genkit.Handler, and the ability to test from the Developer UI and CLI. Any generation call worth keeping should live in a flow. - Use
jsonschema:"description=..."struct tags on output types. The model uses these descriptions to understand what each field should contain. Without them, structured output quality drops significantly. - Write good tool descriptions. The model decides which tools to call based on their description string. Vague descriptions lead to missed or incorrect tool calls.
- Use
.promptfiles for complex prompts. They separate prompt content from Go code, support Handlebars templating, and can be iterated on without recompilation. Code-defined prompts are better for simple, single-line cases. - Reach for built-in middleware before writing one.
Retry,Fallback,ToolApproval,Filesystem, andSkillscover the common cross-cutting needs and compose with each other viaai.WithUse. See references/middleware.md. When you do write custom middleware, allocate per-call state in closures captured byNew, and guard anything thatWrapToolmutates because tools may run concurrently. - Look up the latest model IDs. Model names change frequently. Check provider documentation for current model IDs rather than relying on hardcoded names. See references/providers.md.
FAQ
What does the developing-genkit-go skill do?
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.
How do I install developing-genkit-go?
Run npx skills add https://github.com/firebase/agent-skills --skill developing-genkit-go in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/developing-genkit-go/ (personal) or .claude/skills/developing-genkit-go/ (project).
Which AI agents can use developing-genkit-go?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is developing-genkit-go safe to install?
Security partners have reviewed it: Gen Agent Trust Hub passed; Socket passed; Snyk passed; ZeroLeaks passed. As with any skill, read the SKILL.md and bundled scripts before installing.
Who maintains developing-genkit-go?
It is published by firebase in firebase/agent-skills, and it is an official skill from the maker of the technology it covers. It has 49,492 recorded installs.
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