apify-ultimate-scraper
Raspador web automatizado que selecciona los Actores óptimos para más de 55 plataformas, incluyendo Instagram, TikTok, YouTube, Facebook, Google Maps y más. Cubre más de 55 Actores preconfigurados en 8 plataformas principales con orientación de selección específica para casos de uso (generación de leads, descubrimiento de influencers, monitoreo de marca, análisis de competencia, investigación de tendencias). Admite tres formatos de salida: visualización rápida en chat, exportación CSV o exportación JSON con límites de resultados personalizables. Incluye patrones de flujo de trabajo con múltiples Actores para casos complejos...
npx skills add https://github.com/apify/agent-skills --skill apify-ultimate-scraperUniversal web scraper
AI-driven data extraction from ~100 Actors across 15+ platforms via the Apify CLI.
Rules for every apify command:
- Pass
--jsonfor machine-readable output (stable across CLI versions). - Pass
--user-agent apify-agent-skills/apify-ultimate-scraperfor 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 containsAPIFY_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.