From apify
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.
How this skill is triggered — by the user, by Claude, or both
Slash command
/apify:apify-ultimate-scraperThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
AI-driven data extraction from ~100 Actors across 15+ platforms via the Apify CLI.
references/actor-index.mdreferences/gotchas.mdreferences/workflows/brand-monitoring.mdreferences/workflows/company-research.mdreferences/workflows/competitive-intel.mdreferences/workflows/contact-enrichment.mdreferences/workflows/content-and-seo.mdreferences/workflows/ecommerce-price-monitoring.mdreferences/workflows/influencer-vetting.mdreferences/workflows/job-market-and-recruitment.mdreferences/workflows/knowledge-base-and-rag.mdreferences/workflows/lead-generation.mdreferences/workflows/real-estate-and-hospitality.mdreferences/workflows/review-analysis.mdreferences/workflows/social-media-analytics.mdreferences/workflows/trend-research.mdAI-driven data extraction from ~100 Actors across 15+ platforms via the Apify CLI.
Rule: Pass --json and redirect stderr with 2>/dev/null on data-returning commands (actors call, actors start, actors info, actors search, datasets get-items, runs info). JSON output is stable across CLI versions. stderr contains progress messages and version warnings that break JSON parsers if not redirected.
This rule does not apply to status/auth commands (apify info, apify --version, apify login). For those, use 2>&1 so authentication and version errors are visible.
Exception: if --input returns no data, re-run with 2>&1 to confirm whether the cause is a missing schema vs. a network/auth error.
npm install -g apify-cli)If a CLI command fails with an auth error, authenticate using one of these methods:
apify login (opens browser)export APIFY_TOKEN=your_token_heresource .env (if the file contains APIFY_TOKEN=...)Generate token: https://console.apify.com/settings/integrations
Before using the Apify CLI, always verify the local environment:
apify --help
If this fails, install the CLI first:
npm install -g apify-cli
# Auth check — do NOT pipe to /dev/null, you need to see errors
apify info 2>&1
If this shows the user is not logged in, instruct them to authenticate with a token:
apify login --token TOKEN
Run Apify CLI commands with all permissions when needed by the agent sandbox.
Assume many Apify commands block with zero output until completion. For blocking runs, set block_until_ms to at least 60000.
For long or unknown-duration runs, prefer the async pattern:
apify actors start "ACTOR_ID" -i 'JSON_INPUT' --json 2>/dev/null
Then poll the run status:
apify info actor-runs/RUN_ID --json
Check .status for SUCCEEDED or FAILED.
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" --json --limit 10 2>/dev/null
From results: items[].username/items[].name (Actor ID), items[].title, items[].stats.totalUsers30Days, items[].currentPricingInfo.pricingModel.
Some Actors don't register an input schema with the platform (their schema lives in code). Try schema sources in this order — fall through on empty/error:
apify actors info "ACTOR_ID" --input 2>/dev/null
If output is Error: No input schema found for this Actor, skip to source 2.
apify actors info "ACTOR_ID" --input --json 2>/dev/null | jq '.input.schema.properties // empty | keys'
Empty result means no registered schema — fall through to source 3. To drill into a specific field:
apify actors info "ACTOR_ID" --input --json 2>/dev/null | jq '.input.schema.properties.FIELD_NAME'
apify actors info "ACTOR_ID" --readme 2>/dev/null
Grep the README for an "Input" / "Example input" section to copy the JSON shape.
{"startUrls":[{"url":"..."}]} for crawlers) and let the Actor surface validation errors that reveal required fields. See references/gotchas.md for known-good minimal inputs for common Actors.Also read references/gotchas.md to check for common pitfalls and cost guardrails for the selected Actor.
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.
Before starting the run, double-check whether the task is short enough for a blocking call or should use the async pattern from Step 0.
Standard run (blocking):
apify actors call "ACTOR_ID" -i 'JSON_INPUT' --json 2>/dev/null
From output: .id (run ID), .status, .defaultDatasetId, .stats.durationMillis
Fetch results:
apify datasets get-items DATASET_ID --format json
For CSV: apify datasets get-items DATASET_ID --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" -i 'JSON_INPUT' --json 2>/dev/null
Poll: apify info actor-runs/RUN_ID --json (check .status for SUCCEEDED or FAILED).
Report: result count, file location (if saved), key data fields, and links:
https://console.apify.com/storage/datasets/DATASET_IDhttps://console.apify.com/actors/runs/RUN_IDFor multi-step workflows: suggest the next pipeline step from the workflow guide.
Common errors and pitfalls are documented in references/gotchas.md. Read it before running PPE (pay-per-event) Actors.
Guides creation, editing, and verification of skills for AI coding agents using test-driven development with subagent scenarios. Use when authoring or debugging skills.
npx claudepluginhub apify/apify-claude-code-plugin --plugin apify