Customization

Before executing, check for user customizations at: ~/.claude/skills/CORE/USER/SKILLCUSTOMIZATIONS/Apify/

If this directory exists, load and apply any PREFERENCES.md, configurations, or resources found there. These override default behavior. If the directory does not exist, proceed with skill defaults.

🚨 MANDATORY: Voice Notification (REQUIRED BEFORE ANY ACTION)

You MUST send this notification BEFORE doing anything else when this skill is invoked.

Send voice notification:

curl -s -X POST http://localhost:8888/notify
-H "Content-Type: application/json"
-d '{"message": "Running the WORKFLOWNAME workflow in the Apify skill to ACTION"}' \

/dev/null 2>&1 &

Output text notification:

Running the WorkflowName workflow in the Apify skill to ACTION...

This is not optional. Execute this curl command immediately upon skill invocation.

Apify - Social Media & Web Scraping

Direct TypeScript access to 9 popular Apify actors with 99% token savings.

🔌 File-Based MCP

This skill is a file-based MCP - a code-first API wrapper that replaces token-heavy MCP protocol calls.

Why file-based? Filter data in code BEFORE returning to model context = 97.5% token savings.

Architecture: See ~/.claude/skills/CORE/SYSTEM/DOCUMENTATION/FileBasedMCPs.md

🎯 Overview

Direct TypeScript access to the 9 most popular Apify actors without MCP overhead. Filter and transform data in code BEFORE it reaches the model context.

📊 Available Actors

Social Media (5 platforms)

• Instagram (145k users, 4.60★) - Profiles, posts, hashtags, comments

• LinkedIn (26k users, 4.10★) - Profiles, jobs, posts

• TikTok (90k users, 4.61★) - Profiles, videos, hashtags, comments

• YouTube (40k users, 4.40★) - Channels, videos, comments, search

• Facebook (35k users, 4.56★) - Posts, groups, comments

Business & Lead Generation

• Google Maps (198k users, 4.76★) - HIGHEST VALUE!

• Search businesses, extract contacts, reviews, images

• Perfect for lead generation

E-commerce

• Amazon (8k users, 4.97★) - Products, reviews, pricing

Web Scraping

• Web Scraper (94k users, 4.39★) - General-purpose, works with ANY website

🚀 Quick Start

Basic Usage Pattern

import { scrapeInstagramProfile, searchGoogleMaps } from '~/.claude/skills/Apify/actors'

// 1. Call the actor wrapper const profile = await scrapeInstagramProfile({ username: 'target_username', maxPosts: 50 })

// 2. Filter in code - BEFORE data reaches model! const viral = profile.latestPosts?.filter(p => p.likesCount > 10000)

// 3. Only filtered results reach model context console.log(viral) // ~10 posts instead of 50

📚 Examples by Use Case

Social Media Monitoring

Instagram - Track engagement:

import { scrapeInstagramProfile, scrapeInstagramPosts } from '~/.claude/skills/Apify/actors'

// Get profile with recent posts const profile = await scrapeInstagramProfile({ username: 'competitor', maxPosts: 100 })

// Filter in code - only high-performing posts from last 30 days const thirtyDaysAgo = Date.now() - (30 * 24 * 60 * 60 * 1000) const topRecent = profile.latestPosts ?.filter(p => new Date(p.timestamp).getTime() > thirtyDaysAgo && p.likesCount > 5000 ) .sort((a, b) => b.likesCount - a.likesCount) .slice(0, 10)

// Only 10 posts reach model instead of 100!

LinkedIn - Job search:

import { searchLinkedInJobs } from '~/.claude/skills/Apify/actors'

const jobs = await searchLinkedInJobs({ keywords: 'AI engineer', location: 'San Francisco', remote: true, maxResults: 200 })

// Filter in code - only senior roles at well-funded startups const topJobs = jobs.filter(j => j.seniority?.includes('Senior') && parseInt(j.applicants || '0') > 50 )

TikTok - Trend analysis:

import { scrapeTikTokHashtag } from '~/.claude/skills/Apify/actors'

const videos = await scrapeTikTokHashtag({ hashtag: 'ai', maxResults: 500 })

// Filter in code - only viral content const viral = videos .filter(v => v.playCount > 1000000) .sort((a, b) => b.playCount - a.playCount) .slice(0, 20)

Lead Generation (Business Intelligence)

Google Maps - Local business leads:

import { searchGoogleMaps } from '~/.claude/skills/Apify/actors'

// Search with contact info extraction const places = await searchGoogleMaps({ query: 'restaurants in Austin', maxResults: 500, includeReviews: true, maxReviewsPerPlace: 20, scrapeContactInfo: true // Extracts emails from websites! })

// Filter in code - only highly-rated with email/phone const qualifiedLeads = places .filter(p => p.rating >= 4.5 && p.reviewsCount >= 100 && (p.email || p.phone) ) .map(p => ({ name: p.name, rating: p.rating, reviews: p.reviewsCount, email: p.email, phone: p.phone, website: p.website, address: p.address }))

// Export leads - only qualified results! console.log(Found ${qualifiedLeads.length} qualified leads)

Google Maps - Review sentiment analysis:

import { scrapeGoogleMapsReviews } from '~/.claude/skills/Apify/actors'

const reviews = await scrapeGoogleMapsReviews({ placeUrl: 'https://maps.google.com/maps?cid=12345', maxResults: 1000 })

// Filter in code - analyze sentiment by rating const recentNegative = reviews .filter(r => { const thirtyDaysAgo = Date.now() - (30 * 24 * 60 * 60 * 1000) return ( r.rating <= 2 && new Date(r.publishedAtDate).getTime() > thirtyDaysAgo && r.text.length > 50 ) })

// Identify common complaints const complaints = recentNegative.map(r => r.text)

E-commerce & Competitive Intelligence

Amazon - Price monitoring:

import { scrapeAmazonProduct } from '~/.claude/skills/Apify/actors'

const product = await scrapeAmazonProduct({ productUrl: 'https://www.amazon.com/dp/B08L5VT894', includeReviews: true, maxReviews: 200 })

// Filter in code - only recent negative reviews const recentNegative = product.reviews ?.filter(r => { const weekAgo = Date.now() - (7 * 24 * 60 * 60 * 1000) return ( r.rating <= 2 && new Date(r.date).getTime() > weekAgo ) })

console.log(Price: $${product.price}) console.log(Rating: ${product.rating}/5) console.log(Recent issues: ${recentNegative?.length} complaints)

Custom Web Scraping

Any Website - Custom extraction:

import { scrapeWebsite } from '~/.claude/skills/Apify/actors'

const products = await scrapeWebsite({ startUrls: ['https://example.com/products'], linkSelector: 'a.product-link', maxPagesPerCrawl: 100, pageFunction: ` async function pageFunction(context) { const { request, $, log } = context

  return {
    url: request.url,
    title: $('h1.product-title').text(),
    price: $('span.price').text(),
    inStock: $('.in-stock').length > 0,
    description: $('.description').text()
  }
}

` })

// Filter in code - only available products under $100 const affordable = products.filter(p => p.inStock && parseFloat(p.price.replace('$', '')) < 100 )

🎨 Advanced Patterns

Pattern 1: Multi-Platform Social Listening

import { scrapeInstagramHashtag, scrapeTikTokHashtag, searchYouTube } from '~/.claude/skills/Apify/actors'

// Run all platforms in parallel const [instagramPosts, tiktokVideos, youtubeVideos] = await Promise.all([ scrapeInstagramHashtag({ hashtag: 'ai', maxResults: 100 }), scrapeTikTokHashtag({ hashtag: 'ai', maxResults: 100 }), searchYouTube({ query: '#ai', maxResults: 100 }) ])

// Combine and filter - only viral content across all platforms const allViral = [ ...instagramPosts.filter(p => p.likesCount > 10000), ...tiktokVideos.filter(v => v.playCount > 100000), ...youtubeVideos.filter(v => v.viewsCount > 50000) ]

console.log(Found ${allViral.length} viral posts across 3 platforms)

Pattern 2: Lead Enrichment Pipeline

import { searchGoogleMaps, scrapeLinkedInProfile } from '~/.claude/skills/Apify/actors'

// 1. Find businesses on Google Maps const restaurants = await searchGoogleMaps({ query: 'restaurants in SF', maxResults: 100, scrapeContactInfo: true })

// 2. Filter for qualified leads const qualified = restaurants.filter(r => r.rating >= 4.5 && r.email && r.reviewsCount >= 50 )

// 3. Enrich with LinkedIn data (if available) const enriched = await Promise.all( qualified.map(async (restaurant) => { // Try to find LinkedIn company page // ... additional enrichment logic return restaurant }) )

Pattern 3: Competitive Analysis Dashboard

import { scrapeInstagramProfile, scrapeYouTubeChannel, scrapeTikTokProfile } from '~/.claude/skills/Apify/actors'

async function analyzeCompetitor(username: string) { // Gather data from all platforms const [instagram, youtube, tiktok] = await Promise.all([ scrapeInstagramProfile({ username, maxPosts: 30 }), scrapeYouTubeChannel({ channelUrl: https://youtube.com/@${username}, maxVideos: 30 }), scrapeTikTokProfile({ username, maxVideos: 30 }) ])

// Calculate engagement metrics in code return { username, instagram: { followers: instagram.followersCount, avgLikes: average(instagram.latestPosts?.map(p => p.likesCount) || []), engagementRate: calculateEngagement(instagram) }, youtube: { subscribers: youtube.subscribersCount, avgViews: average(youtube.videos?.map(v => v.viewsCount) || []) }, tiktok: { followers: tiktok.followersCount, avgPlays: average(tiktok.videos?.map(v => v.playCount) || []) } } }

💰 Token Savings Calculator

Example: Instagram profile with 100 posts

MCP Approach:

1. search-actors → 1,000 tokens
2. call-actor → 1,000 tokens
3. get-actor-output → 50,000 tokens (100 unfiltered posts) TOTAL: ~52,000 tokens

File-Based Approach:

const profile = await scrapeInstagramProfile({ username: 'user', maxPosts: 100 })

// Filter in code - only top 10 posts const top = profile.latestPosts ?.sort((a, b) => b.likesCount - a.likesCount) .slice(0, 10)

// TOTAL: ~500 tokens (only 10 filtered posts reach model)

Savings: 99% reduction (52,000 → 500 tokens)

🔧 Actor Reference

Social Media

Instagram

• scrapeInstagramProfile(input)

• Profile + posts

• scrapeInstagramPosts(input)

• Posts from user

• scrapeInstagramHashtag(input)

• Posts by hashtag

• scrapeInstagramComments(input)

• Comments on post

LinkedIn

• scrapeLinkedInProfile(input)

• Profile + experience + email

• searchLinkedInJobs(input)

• Job listings

• scrapeLinkedInPosts(input)

• Posts from profile/company

TikTok

• scrapeTikTokProfile(input)

• Profile + videos

• scrapeTikTokHashtag(input)

• Videos by hashtag

• scrapeTikTokComments(input)

• Comments on video

YouTube

• scrapeYouTubeChannel(input)

• Channel + videos

• searchYouTube(input)

• Search videos

• scrapeYouTubeComments(input)

• Comments on video

Facebook

• scrapeFacebookPosts(input)

• Posts from pages

• scrapeFacebookGroups(input)

• Group posts

• scrapeFacebookComments(input)

• Post comments

Business & Lead Generation

Google Maps

• searchGoogleMaps(input)

• Search places (with contact extraction!)

• scrapeGoogleMapsPlace(input)

• Single place details

• scrapeGoogleMapsReviews(input)

• Place reviews

E-commerce

Amazon

• scrapeAmazonProduct(input)

• Product details + reviews

• scrapeAmazonReviews(input)

• Product reviews only

Web Scraping

General Web

• scrapeWebsite(input)

• Custom multi-page crawling

• scrapePage(url, pageFunction)

• Single page extraction

⚙️ Configuration

Environment Variables:

Required - Get from https://console.apify.com/account/integrations

APIFY_TOKEN=apify_api_xxxxx...

Actor Run Options:

{ memory: 2048, // MB: 128, 256, 512, 1024, 2048, 4096, 8192 timeout: 300, // seconds build: 'latest' // or specific build number }

🎯 When to Use This vs MCP

Use File-Based (this skill):

• ✅ Need to filter large datasets (>100 results)

• ✅ Want to transform/aggregate data in code

• ✅ Multiple sequential operations

• ✅ Control flow (loops, conditionals)

• ✅ Maximum token efficiency

Use MCP:

• ❌ Simple single operations with small results (<10 items)

• ❌ One-off exploratory queries

• ❌ Don't want to write code

🔗 Links

• Apify Platform: https://apify.com

• Actor Store: https://apify.com/store

• API Docs: https://docs.apify.com/api/v2

Remember: Filter data in code BEFORE returning to model context. This is where the 99% token savings happen!