apify-ultimate-scraper

name apify-ultimate-scraper description 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. Universal web scraper AI-driven data extraction from ~100 Actors across 15+ platforms via the Apify CLI. Rules for every apify command: Pass --json for machine-readable output (stable across CLI versions). Pass --user-agent apify-agent-skills/apify-ultimate-scraper for telemetry attribution. Redirect stderr with 2>/dev/null (stderr contains progress messages that break JSON parsers). Prerequisites Apify CLI v1.5.0+ ( npm install -g apify-cli ) Authenticated session (see below) Authentication If a CLI command fails with an auth error, authenticate using one of these methods: OAuth (interactive): apify login (opens browser) Environment variable: export APIFY_TOKEN=your_token_here From .env file: source .env (if the file contains APIFY_TOKEN=... ) Generate token: https://console.apify.com/settings/integrations Workflow Step 1: Understand goal and select Actor Identify the target platform and use case. Read references/actor-index.md to find the right Actor. If the task involves a multi-step pipeline, also read the matching workflow guide: Task involves... Read leads, contacts, emails, B2B references/workflows/lead-generation.md competitor, ads, pricing references/workflows/competitive-intel.md influencer, creator references/workflows/influencer-vetting.md brand, mentions, sentiment references/workflows/brand-monitoring.md reviews, ratings, reputation references/workflows/review-analysis.md SEO, SERP, crawl, content, RAG references/workflows/content-and-seo.md analytics, engagement, performance references/workflows/social-media-analytics.md trends, keywords, hashtags references/workflows/trend-research.md jobs, recruiting, candidates references/workflows/job-market-and-recruitment.md real estate, listings, hotels references/workflows/real-estate-and-hospitality.md price monitoring, e-commerce, products references/workflows/ecommerce-price-monitoring.md contact enrichment, email extraction references/workflows/contact-enrichment.md knowledge base, RAG, LLM data feed references/workflows/knowledge-base-and-rag.md company research, due diligence references/workflows/company-research.md If no Actor matches in the index, search dynamically: apify actors search "KEYWORDS" --user-agent apify-agent-skills/apify-ultimate-scraper --json --limit 10 2>/dev/null From results: items[].username / items[].name (Actor ID), items[].title , items[].stats.totalUsers30Days , items[].currentPricingInfo.pricingModel . Step 2: Fetch Actor schema and check gotchas Fetch the input schema dynamically: apify actors info "ACTOR_ID" --user-agent apify-agent-skills/apify-ultimate-scraper --input --json 2>/dev/null Also read references/gotchas.md to check for common pitfalls for the selected Actor. For Actor documentation: apify actors info "ACTOR_ID" --user-agent apify-agent-skills/apify-ultimate-scraper --readme Step 3: Configure and run Skip user preferences for simple lookups (e.g., "Nike's follower count"). Go straight to running with quick answer mode. For larger tasks, confirm output format (quick answer / CSV / JSON) and result count. Standard run (blocking): apify actors call "ACTOR_ID" --input-file input.json --user-agent apify-agent-skills/apify-ultimate-scraper --json 2>/dev/null Prefer --input-file input.json for large or complex inputs. For tiny inputs, inline JSON is acceptable with shell quoting: --input '{"maxItems":10}' . From output: .id (run ID), .status , .defaultDatasetId , .stats.durationMillis Fetch results: apify datasets get-items DATASET_ID --user-agent apify-agent-skills/apify-ultimate-scraper --format json For CSV: apify datasets get-items DATASET_ID --user-agent apify-agent-skills/apify-ultimate-scraper --format csv Quick answer mode: Fetch results as JSON, pick top 5, present formatted in chat. Save to file: Fetch results, use Write tool to save as YYYY-MM-DD_descriptive-name.csv or .json . Large/long-running scrapes: apify actors start "ACTOR_ID" --input-file input.json --user-agent apify-agent-skills/apify-ultimate-scraper --json 2>/dev/null Poll: apify runs info RUN_ID --user-agent apify-agent-skills/apify-ultimate-scraper --json 2>/dev/null (check .status for SUCCEEDED ). Step 4: Deliver results Report: result count, file location (if saved), key data fields, and links: Dataset: https://console.apify.com/storage/datasets/DATASET_ID Run: https://console.apify.com/actors/runs/RUN_ID For multi-step workflows: suggest the next pipeline step from the workflow guide. Troubleshooting Common errors and pitfalls are documented in references/gotchas.md . Read it before running PPE (pay-per-event) Actors.