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/apify-ultimate-scraper

@97047d3 official
by apifyapify/agent-skills2.4k stars
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Universal AI-powered web scraper for any platform. Scrape data from Instagram, Facebook, TikTok, YouTube, LinkedIn, X/Twitter, Google Maps, Google Search, Google Trends, Reddit, Airbnb, Yelp, and 15+ more platforms. Use for lead generation, brand monitoring, competitor analysis, influencer discovery, trend research, content analytics, audience analysis, review analysis, SEO intelligence, recruitment, or any data extraction task.

Use this Skill: https://skilld.dev/gh/apify/agent-skills/apify-ultimate-scraper

This session only. Nothing lands on disk.

referencesworkflowssocial-media-analytics.md

≈833 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Social media analytics workflows

Instagram account performance analysis

When: User wants engagement metrics and content performance for an Instagram account.

Pipeline

  1. Get profile -> apify/instagram-profile-scraper
    • Key input: usernames
  2. Get recent posts -> apify/instagram-post-scraper
    • Key input: directUrls (from profile's latestPosts[].url) or usernames

Output fields

Step 1: followersCount, followsCount, postsCount, biography, isVerified Step 2: caption, likesCount, commentsCount, timestamp, type (photo/video/reel), url

TikTok creator analytics

When: User wants performance data for a TikTok creator.

Pipeline

  1. Get profile -> clockworks/tiktok-profile-scraper
    • Key input: profiles (handles or URLs)

Output fields

Step 1: nickname, followers, following, likes, videos, verified, recentVideos[] (with views, likes, shares per video)

Instagram competitor content analysis

When: User wants to identify top-performing content formats and engagement patterns from competitor Instagram accounts.

Pipeline

  1. Get competitor posts -> apify/instagram-post-scraper
    • Key input: usernames (competitor handles), resultsLimit (100), scrapePostsUntilDate
  2. Get reels separately -> apify/instagram-reel-scraper
    • Key input: usernames (same handles)

Output fields

Step 1: likesCount, commentsCount, timestamp, type (post/reel/story), caption, displayUrl, url Step 2: likesCount, commentsCount, playsCount, duration, caption, url

Gotcha

Run both Actors to capture full content mix - the post scraper may under-count reels. Calculate engagement rate per post (likes + comments / follower count) and sort to surface top performers.

LinkedIn company page analytics

When: User wants to track LinkedIn post performance for a company page or benchmark against competitors.

Pipeline

  1. Get company posts -> harvestapi/linkedin-company-posts
    • Key input: companyUrl, maxPosts, publishedAfter
  2. Enrich post details -> apimaestro/linkedin-post-detail
    • Pipe: results[].url -> urls

Output fields

Step 1: likesCount, commentsCount, repostsCount, text, publishedAt, url Step 2: reactions{} (breakdown by type), topComments[], impressions

Gotcha

Both Actors are PPE. Step 1: ~$0.002/post, Step 2: ~$0.005/post. For 100 posts across 3 companies, estimate ~$2.10. Confirm with user before running.

Multi-platform engagement comparison

When: User wants to compare an account's performance across platforms.

Pipeline (run independently, combine)

  1. Instagram -> apify/instagram-profile-scraper with usernames
  2. TikTok -> clockworks/tiktok-profile-scraper with profiles
  3. YouTube -> streamers/youtube-channel-scraper with channelUrls
  4. X/Twitter -> apidojo/twitter-user-scraper with handles

Output fields

Instagram: followersCount, postsCount, biography TikTok: followers, likes, videos YouTube: subscriberCount, videoCount, viewCount X/Twitter: followers, tweets, likes

Gotcha

Parallel workflow - run each Actor independently. Normalize metric names for comparison (followers/subscribers, posts/videos/tweets).

Source: SKILL.md on GitHub

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  • Gen Agent Trust Hub16d

    The skill provides comprehensive instructions for orchestrating and interacting with web scrapers (Actors) via the Apify CLI. It provides structured playbooks for different data extraction workflows (B2B lead generation, brand monitoring, social media analytics, etc.) and contains standard guidelines on configuration, parameter passing, and error handling. No malicious behaviors, obfuscation techniques, or hidden actions were detected.

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    Risk: MEDIUM · 1 issue

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    Score: 93/100 · 2 sections analyzed

Signed by skilld at 97047d3. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

Activeupdated 3 months ago
  • SEO
  • apify
  • scraping
  • web-scraping
  • instagram
  • facebook
  • tiktok
  • youtube
  • linkedin
  • twitter
  • google-maps
  • reddit
  • lead-generation
  • competitor-analysis
  • brand-monitoring

README badge

README badge for apify/agent-skills/apify-ultimate-scraper

Scrapes data from 100+ Apify Actors covering Instagram, Facebook, TikTok, YouTube, LinkedIn, X/Twitter, Google Maps, Reddit, Airbnb, Yelp, and 15+ other platforms via the Apify CLI. Use for lead generation, competitor analysis, brand monitoring, influencer discovery, review analysis, or SEO intelligence on any public web platform.

Generated from the current SKILL.md.

Does this skill work with all platforms?
It covers ~100 Actors across 15+ platforms including Instagram, Facebook, TikTok, YouTube, LinkedIn, X/Twitter, Google Maps, Reddit, Airbnb, Yelp, and more. Not all platforms are equally supported; check the actor-index.md reference for your target platform.
What authentication is required?
You need an Apify account and CLI token. Authenticate via `apify login` (OAuth), set `APIFY_TOKEN` as an environment variable, or source from a .env file.
Do I need to install anything locally?
Yes, Apify CLI v1.5.0 or later must be installed via npm (`npm install -g apify-cli`).
Can I export results in different formats?
Yes. Results can be fetched as JSON or CSV using `apify datasets get-items` with the `--format` flag.
What should I read before running a scraper for the first time?
Check `references/actor-index.md` to find the right Actor for your platform, then read `references/gotchas.md` for common pitfalls specific to that Actor before running.

Generated from the current SKILL.md. These answers refresh after source changes.