Scripts by johnlindquist

// Name: Customer.io Top Clicked Links
// Description: Get the top clicked links for my AI Dev Essentials newsletter

// You can find the newsletter here:
// https://egghead.io/newsletters/ai-dev-essentials

import "@johnlindquist/kit"

// Prompt (or load) your Customer.io App (not tracking) API key
const API_KEY = await env('CIO_API_KEY')

// Customer.io App API base (US region). Remove the extra /api segment
const API_BASE = 'https://api.customer.io/v1'

/**
 * Shape of each newsletter returned by the `/newsletters` endpoint.
 */
interface NewsletterSummary {
    id: number
    name: string

// Name: Stripe Payment Links
// Description: Fetch payment links from Stripe and retrieve customer emails from successful payments
// Author: johnlindquist

import "@johnlindquist/kit"
import Stripe from "stripe"

// Get Stripe API key from environment
const STRIPE_API_KEY = await env("STRIPE_API_KEY", {
    secret: true,
    hint: "Enter your Stripe secret key (sk_live_...)"
})

// Initialize Stripe SDK
const stripe = new Stripe(STRIPE_API_KEY)

// Fetch all payment links from Stripe
const fetchPaymentLinks = async (): Promise<Stripe.PaymentLink[]> => {
    const links: Stripe.PaymentLink[] = []
    for await (const link of stripe.paymentLinks.list()) {

// Name: Select and Play Audio File
// Description: Select an audio file from your system and play it
// Author: johnlindquist

import "@johnlindquist/kit"

let audioFile = await selectFile("Select an audio file to play")

if (!audioFile) {
  await div(md("No file selected"))
  exit()
}

// Check if the selected file is an audio file
const audioExtensions = ['.mp3', '.wav', '.m4a', '.aac', '.ogg', '.flac', '.wma']
const fileExtension = path.extname(audioFile).toLowerCase()

if (!audioExtensions.includes(fileExtension)) {
  await div(md(`**${path.basename(audioFile)}** is not a supported audio file format.
  

// Name: Random Choices Showcase
// Description: Demonstrates all possible choice options and configurations in Script Kit
// Author: johnlindquist

import "@johnlindquist/kit"

// Generate random data for demonstrations
const generateRandomChoices = (count = 10) => {
  const adjectives = ['Amazing', 'Brilliant', 'Creative', 'Dynamic', 'Elegant', 'Fantastic', 'Gorgeous', 'Incredible', 'Magnificent', 'Outstanding']
  const nouns = ['Script', 'Widget', 'Tool', 'App', 'Feature', 'Component', 'Module', 'Function', 'Service', 'Platform']
  const colors = ['red', 'blue', 'green', 'purple', 'orange', 'pink', 'yellow', 'cyan', 'magenta', 'lime']
  
  return Array.from({ length: count }, (_, i) => ({
    name: `${adjectives[i % adjectives.length]} ${nouns[i % nouns.length]} ${i + 1}`,
    value: `choice-${i + 1}`,
    description: `This is a detailed description for choice ${i + 1} with lots of helpful information`,
    tag: colors[i % colors.length],
    shortcut: i < 5 ? `cmd+${i + 1}` : undefined,
    icon: i % 3 === 0 ? '🎯' : i % 3 === 1 ? '⭐' : '🚀',
    preview: () => `<div class="p-4 bg-gradient-to-r from-${colors[i % colors.length]}-400 to-${colors[(i + 1) % colors.length]}-600 text-white rounded-lg">

// Name: Export Reddit Bookmarks
// Description: Grab all Reddit bookmarks from the past week and save as JSON
// Author: johnlindquist

import "@johnlindquist/kit"

// Get Reddit API credentials
const REDDIT_CLIENT_ID = await env("REDDIT_CLIENT_ID", {
  hint: "Get from https://www.reddit.com/prefs/apps - create a 'script' app",
})
const REDDIT_CLIENT_SECRET = await env("REDDIT_CLIENT_SECRET", {
  hint: "Secret from your Reddit app",
  secret: true,
})
const REDDIT_USERNAME = await env("REDDIT_USERNAME")
const REDDIT_PASSWORD = await env("REDDIT_PASSWORD", {
  hint: "Your Reddit password",
  secret: true,
})

// Name: AI-Powered Text Processor
// Description: Process and transform text using AI with various operations
// Author: Script Kit User

import "@johnlindquist/kit"

// Get text from user - either selected text or manual input
let inputText = await getSelectedText()

if (!inputText?.trim()) {
  inputText = await editor({
    placeholder: "Enter text to process...",
    hint: "Type or paste text that you want to transform using AI"
  })
}

if (!inputText?.trim()) {
  await div(md("No text provided. Exiting..."))
  exit()
}

// Name: AI-Powered File Inspector
// Description: Use AI to analyze and organize files with smart categorization and human-like descriptions
// Author: johnlindquist

import '@johnlindquist/kit'
import { OpenAI } from 'openai'

interface FileAnalysis {
  path: string
  name: string
  type: string
  size: number
  aiDescription: string
  suggestedCategory: string
  confidence: number
}

// Initialize OpenAI client
const openai = new OpenAI({
  apiKey: await env('OPENAI_API_KEY', {

// Name: Video Study Notes Generator
// Description: Records screen, transcribes content, and generates structured study notes
// Author: johnlindquist
// Twitter: @johnlindquist

import '@johnlindquist/kit'

// Setup recording directory
const recordingsPath = createPathResolver(kenvPath('study-recordings'))
await ensureDir(recordingsPath())

// Get study topic from user
const studyTopic = await arg('What are you studying today?')

// Create timestamp for file naming
const timestamp = formatDate(new Date(), 'yyyy-MM-dd-HH-mm-ss')
const baseFileName = `${studyTopic.replace(/[^a-zA-Z0-9]/g, '-')}-${timestamp}`

// Start screen recording with AppleScript
await div({

// Name: Hello World
// Description: Simple hello world script that greets the user by name
// Author: johnlindquist
// Twitter: @johnlindquist

import "@johnlindquist/kit"

const result = await arg("What's your name?")

await notify(`Hello, ${result}!`)

import '@johnlindquist/kit'
import Jimp from 'jimp'

let downloadsPath = home('Downloads')
let files = await readdir(downloadsPath)
let pngFiles = files.filter(file => file.toLowerCase().endsWith('.png'))

let filesWithStats = []
for (let pngFile of pngFiles) {
  let filePath = path.join(downloadsPath, pngFile)
  let stats = await stat(filePath)
  filesWithStats.push({ path: filePath, stats })
}

filesWithStats.sort((a, b) => b.stats.mtimeMs - a.stats.mtimeMs)

let latestTwoImages = filesWithStats.slice(0, 2)

if (latestTwoImages.length < 2) {
  await div(md(`## Not enough PNG images found in Downloads`))

// Name: Barbarian Chat
// Description: Chat with an AI Barbarian
// Author: Bard

import '@johnlindquist/kit'import { ChatOpenAI } from '@langchain/openai'
import { ChatPromptTemplate, MessagesPlaceholder } from '@langchain/core/prompts'
import { START, END, MessagesAnnotation, StateGraph, MemorySaver } from '@langchain/langgraph'
import { trimMessages } from '@langchain/core/messages'

let id: NodeJS.Timeout | number = -1;
let currentMessage: string = ``;

const llm = new ChatOpenAI({
  modelName: 'gpt-4o-mini',
  apiKey: await env('OPENAI_API_KEY'),
  temperature: 0.7,
  streaming: true,
  callbacks: [
    {
      handleLLMStart: async () => {

// Author: johnlindquist

// Name: Batch Image Renamer
// Description: Rename images in a directory with Faker-generated names
// Author: johnlindquist

import '@johnlindquist/kit'
import { faker } from '@faker-js/faker'

// Prompt user to select a directory containing images
const imageDir = await path({
  onlyDirs: true,
  placeholder: 'Select a directory with images to rename',
})

// Read files from the selected directory
const imageFiles = await readdir(imageDir)
  .then(files => files.filter(file => /\.(jpe?g|png|gif)$/i.test(file))) // Filter for common image types
  .catch(error => {
    console.error('Error reading directory:', error)