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Apify

/Apify

Zbiera dane z mediów społecznościowych, firm i sklepów przez aktory Apify i aktualizuje ich katalog.

Repozytorium
pai ↗
Licencja
MIT
Ostatnia zmiana repozytorium
09.06.2026

Ocena i bezpieczeństwo

95/ 100Klasa: dobry
Format20 / 25
Frontmatter z nazwą i opisem, poprawna nazwa, opis do 1024 znaków, nazwa zgodna z folderem.
Odkrywalność25 / 25
Opis mówi, kiedy użyć skilla, ma sensowną długość i jest w 3. osobie.
Treść35 / 35
Co najmniej 150 słów i do 500 linii, nagłówki, listy kroków, przykłady albo kod.
Higiena15 / 15
Bez zaślepek typu TODO, bez ścieżek Windows, z licencją.
Ryzykobrak sygnałów w skanie
Pliki w paczce
28
Skrypty
21
Komentarze HTML
0
Adresy URL w SKILL.md
9
Przestarzałość

Brak sygnałów. Repozytorium zmienione 09.06.2026, bez odwołań do wycofanych modeli i API.

Licencja

MIT, otwarta: można używać i zmieniać, z zachowaniem informacji o autorze.

Co sprawdzić przed instalacją
  • 21 skryptów w paczce. Przejrzyj je przed instalacją, bo Claude może je uruchomić.

Skrypty: actors/business/google-maps.ts, actors/business/index.ts, actors/ecommerce/amazon.ts, actors/ecommerce/index.ts, actors/index.ts, actors/social-media/facebook.ts, actors/social-media/index.ts, actors/social-media/instagram.ts, actors/social-media/linkedin.ts, actors/social-media/tiktok.ts, actors/social-media/twitter.ts, actors/social-media/youtube.ts, actors/web/index.ts, actors/web/web-scraper.t

Co robi i kiedy

Zbiera dane z mediów społecznościowych, firm i sklepów przez aktory Apify i aktualizuje ich katalog.

Oryginalny opis (EN)

Social media scraping, business data, e-commerce via Apify actors — with auto-update workflow for actor catalog. USE WHEN Twitter, Instagram, LinkedIn, TikTok, YouTube, Facebook, Google Maps, Amazon scraping, Apify, update Apify actors, social media scraping, lead generation, web scraper.

Jak działa

  1. Customization
  2. 🚨 MANDATORY: Voice Notification (REQUIRED BEFORE ANY ACTION)
  3. 🔌 File-Based MCP
  4. 🎯 Overview
  5. 📊 Available Actors
  6. 🚀 Quick Start
  7. 📚 Examples by Use Case
  8. 🎨 Advanced Patterns
  9. 💰 Token Savings Calculator
  10. 🔧 Actor Reference
Sekcje z nagłówków SKILL.md, w oryginale · 477 linii, 1 610 słów
Podgląd SKILL.md
---
name: Apify
description: Social media scraping, business data, e-commerce via Apify actors — with auto-update workflow for actor catalog. USE WHEN Twitter, Instagram, LinkedIn, TikTok, YouTube, Facebook, Google Maps, Amazon scraping, Apify, update Apify actors, social media scraping, lead generation, web scraper.
---

## Customization

**Before executing, check for user customizations at:**
`~/.claude/PAI/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.**

1. **Send voice notification**:
   ```bash
   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 &
   ```

2. **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/PAI/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

```typescript
import { scrapeInstagramProfile, searchGoogleMaps } from '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:**
```typescript
import { scrapeInstagramProfile, scrapeInstagramPosts } from '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:**
```typescript
import { searchLinkedInJobs } from '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:**
```typescript
import { scrapeTikTokHashtag } from '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:**
```typescript
import { searchGoogleMaps } from '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:**
```typescript
import { scrapeGoogleMapsReviews } from '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:**
```typescript
import { scrapeAmazonProduct } from '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:**
```typescript
import { scrapeWebsite } from '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

```typescript
import {
  scrapeInstagramHashtag,
  scrapeTikTokHashtag,
  searchYouTube
} from '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

```typescript
import { searchGoogleMaps, scrapeLinkedInProfile } from '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

```typescript
import {
  scrapeInstagramProfile,
  scrapeYouTubeChannel,
  scrapeTikTokProfile
} from '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:**
```typescript
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:**
```bash
# Required - Get from https://console.apify.com/account/integrations
APIFY_TOKEN=apify_api_xxxxx...
```

**Actor Run Options:**
```typescript
{
  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!**
Pliki w paczce (28)
  • .gitignore 1 KB
  • INTEGRATION.md 6 KB
  • README.md 8 KB
  • SKILL.md 13 KB
  • index.ts 6 KB
  • package.json 1 KB
  • tsconfig.json 1 KB
  • Workflows/Update.md 2 KB
  • actors/index.ts 1 KB
  • actors/business/google-maps.ts 11 KB
  • actors/business/index.ts 1 KB
  • actors/ecommerce/amazon.ts 6 KB
  • actors/ecommerce/index.ts 1 KB
  • actors/social-media/facebook.ts 7 KB
  • actors/social-media/index.ts 1 KB
  • actors/social-media/instagram.ts 9 KB
  • actors/social-media/linkedin.ts 8 KB
  • actors/social-media/tiktok.ts 8 KB
  • actors/social-media/twitter.ts 8 KB
  • actors/social-media/youtube.ts 8 KB
  • actors/web/index.ts 1 KB
  • actors/web/web-scraper.ts 6 KB
  • examples/comparison-test.ts 8 KB
  • examples/instagram-scraper.ts 5 KB
  • examples/smoke-test.ts 2 KB
  • skills/get-user-tweets.ts 3 KB
  • types/common.ts 2 KB
  • types/index.ts 1 KB

Wersje

RepozytoriumWynikLicencja
Ta strona · virtualian/pai95MIT
virtualian/pai95MIT
virtualian/pai95MIT
virtualian/pai95MIT
virtualian/pai95MIT
virtualian/pai95MIT
virtualian/pai95MIT
danielmiessler/LifeOS90MIT

Identyczna treść występuje jeszcze w 2 innych folderach na GitHubie. Tu pokazujemy jedną, najlepiej ocenioną kopię.

Migawka bazy z 28.10.2026 · wersja paczki 33bbb6534da8 (skrót SHA-256 całej paczki)

Zgłoś problem z tym skillem: szkodliwa treść, błędny opis albo prośba autora o usunięcie.

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Uwagi i zgłoszenia

Wiadomość trafi do Bartosza Sokolińskiego. Adres e-mail jest potrzebny tylko do odpowiedzi. Szczegóły w polityce prywatności.