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The recommended way to get started is the CLI. The JavaScript SDK is an optional, advanced path for developers building custom AI agents programmatically.
Use this option to integrate Actionbook directly into your custom AI agents built with any LLM framework.

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Integration Examples

import { Actionbook } from '@actionbookdev/sdk'
import { generateText, tool } from 'ai'
import { openai } from '@ai-sdk/openai'

const actionbook = new Actionbook()

const { text } = await generateText({
  model: openai('gpt-4o'),
  tools: {
    searchActions: tool({
      description: actionbook.searchActions.description,
      parameters: actionbook.searchActions.params.zod,
      execute: async ({ query }) => actionbook.searchActions(query),
    }),
    getActionById: tool({
      description: actionbook.getActionById.description,
      parameters: actionbook.getActionById.params.zod,
      execute: async ({ id }) => actionbook.getActionById(id),
    }),
  },
  maxSteps: 5,
  prompt: 'Search for LinkedIn message actions and get the action manual',
})

import { Actionbook } from '@actionbookdev/sdk'
import OpenAI from 'openai'

const actionbook = new Actionbook()
const openai = new OpenAI()

const tools: OpenAI.ChatCompletionTool[] = [
  {
    type: 'function',
    function: {
      name: 'searchActions',
      description: actionbook.searchActions.description,
      parameters: actionbook.searchActions.params.json,
    },
  },
  {
    type: 'function',
    function: {
      name: 'getActionById',
      description: actionbook.getActionById.description,
      parameters: actionbook.getActionById.params.json,
    },
  },
]

const completion = await openai.chat.completions.create({
  model: 'gpt-4o',
  tools,
  messages: [{ role: 'user', content: 'Search for Google login actions' }],
})

import { Actionbook } from '@actionbookdev/sdk'
import Anthropic from '@anthropic-ai/sdk'

const actionbook = new Actionbook()
const anthropic = new Anthropic()

const tools: Anthropic.Tool[] = [
  {
    name: 'searchActions',
    description: actionbook.searchActions.description,
    input_schema: actionbook.searchActions.params.json,
  },
  {
    name: 'getActionById',
    description: actionbook.getActionById.description,
    input_schema: actionbook.getActionById.params.json,
  },
]

const message = await anthropic.messages.create({
  model: 'claude-sonnet-4-20250514',
  max_tokens: 1024,
  tools,
  messages: [{ role: 'user', content: 'Search for Twitter post actions' }],
})

import { Actionbook } from '@actionbookdev/sdk'
import { GoogleGenAI } from '@google/genai'

const actionbook = new Actionbook()
const genai = new GoogleGenAI({ apiKey: process.env.GEMINI_API_KEY })

const tools = [
  {
    functionDeclarations: [
      {
        name: 'searchActions',
        description: actionbook.searchActions.description,
        parameters: actionbook.searchActions.params.json,
      },
      {
        name: 'getActionById',
        description: actionbook.getActionById.description,
        parameters: actionbook.getActionById.params.json,
      },
    ],
  },
]

const response = await genai.models.generateContent({
  model: 'gemini-2.0-flash',
  contents: [{ role: 'user', parts: [{ text: 'Search for YouTube upload actions' }] }],
  config: { tools },
})

import { Actionbook } from '@actionbookdev/sdk'
import { tool } from 'ai'

const actionbook = new Actionbook()

const agent = stagehand.agent({
  model: 'openai/gpt-4o',
  tools: {
    searchActions: tool({
      description: actionbook.searchActions.description,
      inputSchema: actionbook.searchActions.params.zod,
      execute: async ({ query }) => actionbook.searchActions(query),
    }),
    getActionById: tool({
      description: actionbook.getActionById.description,
      inputSchema: actionbook.getActionById.params.zod,
      execute: async ({ id }) => actionbook.getActionById(id),
    }),
  },
})

await agent.execute('Search for Airbnb booking actions and get the action manual')

​
Installation

# Using npm
npm install @actionbookdev/sdk

# Using pnpm
pnpm add @actionbookdev/sdk

# Using yarn
yarn add @actionbookdev/sdk

# Using bun
bun add @actionbookdev/sdk

​
Basic Usage

import { Actionbook } from '@actionbookdev/sdk'

// Initialize the client (no API key required during open beta)
const actionbook = new Actionbook()

// Search for action manuals
const results = await actionbook.searchActions('airbnb search')
console.log(`Found ${results.length} actions:`, results)

// Get a specific action by ID
const action = await actionbook.getActionById(results[0].id)
console.log('Action details:', action)

// Access the selectors
const selector =
  action.selectors.css ||
  action.selectors.dataTestId ||
  action.selectors.ariaLabel

console.log('Use this selector:', selector)

​
Tool Definitions

Each method has description and params attached for easy integration with any LLM framework. 
import { Actionbook } from '@actionbookdev/sdk'

const actionbook = new Actionbook()

// Description
actionbook.searchActions.description // "Search for action manuals by keyword"

// Params - JSON Schema format
actionbook.searchActions.params.json // { type: "object", properties: { query: { type: "string" } }, required: ["query"] }

// Params - Zod format
actionbook.searchActions.params.zod // z.object({ query: z.string() })