Apify Ultimate Scraper
ApifyOfficialPublished by Apify
- Skill
- Tool integration
- Automation and integrations
- Apache-2.0
- Low risk
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
The apify-ultimate-scraper skill provides a structured, AI-assisted approach to web data extraction. It leverages the Apify CLI to interact with a wide range of platform-specific Actors, ensuring consistent telemetry, machine-readable output, and cost-conscious execution. The skill includes a comprehensive index for selecting the right tool for tasks ranging from social media analytics to e-commerce price monitoring, while enforcing safety protocols for cost estimation and error handling.
What it does
- Provides a standardized CLI workflow for searching, configuring, and running web scrapers.
- Ensures machine-readable output by enforcing JSON formatting and stderr redirection.
- Includes a cost estimation protocol for pay-per-event (PPE) Actors to prevent unexpected billing.
- Facilitates dynamic retrieval of Actor input schemas and documentation.
- Supports both synchronous execution for quick lookups and asynchronous polling for large-scale scrapes.
- Integrates with a library of workflow guides for specific use cases like lead generation and SEO.
When to use it
- When you need to extract structured data from social media, e-commerce, or search engine platforms.
- When performing competitive intelligence, brand monitoring, or market research.
- When you require a repeatable, automated pipeline for data collection.
- When you need to verify the cost implications of a scraping task before execution.
Advantages
- Reduces manual configuration errors through standardized CLI usage patterns.
- Prevents budget overruns with built-in cost estimation and warning thresholds.
- Provides a unified interface for interacting with over 100 different scraping tools.
- Ensures stable, parseable output for downstream data processing.
Usage examples
- “Find a scraper for Instagram follower counts.”
- The agent searches the Actor index, identifies 'apify/instagram-followers-count-scraper', and provides the command to fetch its input schema.
- “Scrape the top 50 results for 'AI tools' on Google Search.”
- The agent selects the appropriate Google Search Actor, estimates the cost if applicable, runs the scrape, and presents the results as a formatted JSON list.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/apify/apify-ultimate-scraper/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip apify-ultimate-scraper.zip -d .agents/skills
Documentation by Apify
Universal 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_hereFrom .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/nullFrom 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/nullAlso 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/nullPrefer --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 jsonFor 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/nullPoll: 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_IDRun:
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.
Files
- ATTRIBUTION.mdAdded by AutoGineer967 B
- LICENSEAdded by AutoGineer10.0 KiB
- SKILL.md5.3 KiB
- references/actor-index.md9.7 KiB
- references/gotchas.md7.3 KiB
- references/workflows/brand-monitoring.md3.7 KiB
- references/workflows/company-research.md4.6 KiB
- references/workflows/competitive-intel.md3.5 KiB
- references/workflows/contact-enrichment.md3.6 KiB
- references/workflows/content-and-seo.md5.1 KiB
- references/workflows/ecommerce-price-monitoring.md4.4 KiB
- references/workflows/influencer-vetting.md3.9 KiB
- references/workflows/job-market-and-recruitment.md3.5 KiB
- references/workflows/knowledge-base-and-rag.md3.7 KiB
- references/workflows/lead-generation.md5.2 KiB
- references/workflows/real-estate-and-hospitality.md3.7 KiB
- references/workflows/review-analysis.md4.1 KiB
- references/workflows/social-media-analytics.md3.3 KiB
- references/workflows/trend-research.md3.3 KiB
references/workflows/job-market-and-recruitment.md
Job market and recruitment workflows
Job listing research
When: User wants to find and analyze job postings by role, company, or location.
Pipeline
Search jobs ->
harvestapi/linkedin-job-searchKey input:
keyword,location,datePosted,limit
Get job details ->
apimaestro/linkedin-job-detailPipe:
results[].jobUrl->urlsKey input:
urls
Output fields
Step 1: title, company, location, jobUrl, postedDate, applicantsCount
Step 2: description, requirements, seniority, employmentType, salary
Gotcha
Both Actors are PPE. Step 1: ~$0.001/job. Step 2: ~$0.005/job. For 200 jobs, total ~$1.20. Estimate and confirm with user.
Candidate sourcing
When: User wants to find potential candidates matching specific criteria.
Pipeline
Search profiles ->
harvestapi/linkedin-profile-searchKey input:
keyword,title,location,industry,limit
Enrich with details ->
apimaestro/linkedin-profile-full-sections-scraperPipe:
results[].profileUrl->urlsKey input:
urls
Output fields
Step 1: fullName, headline, location, profileUrl, currentCompany
Step 2: experience[], education[], skills[], certifications[], languages[]
Gotcha
Step 2 (apimaestro/linkedin-profile-full-sections-scraper) costs ~$0.01/profile - the most expensive LinkedIn scraper. Use sparingly for shortlisted candidates only.
Sales signal outreach - job posting as buying signal
When: User wants to monitor company job postings as a signal to identify sales opportunities - e.g., a "Head of Data Engineering" hire suggests budget for data tooling.
Pipeline
Monitor target postings ->
harvestapi/linkedin-job-searchKey input:
searchUrl(LinkedIn Jobs URL with company or role filters),keywords
Get company context ->
harvestapi/linkedin-companyPipe:
results[].companyUrl->companyUrls
Output fields
Step 1: title, companyName, description, employmentType, seniorityLevel, jobUrl
Step 2: name, industry, employeeCount, description, specialties[]
Gotcha
Job descriptions contain implicit buying signals - tech stack mentions, pain points, and headcount growth. Pass description to an LLM to extract inferred tech stack and budget tier before prioritizing outreach. Contact finding (Hunter.io) uses the native n8n node, not an Apify Actor.
Upwork job monitoring for freelancers
When: User wants to continuously monitor Upwork for new jobs matching their skills.
Pipeline
Scrape Upwork search ->
apify/playwright-scraperKey input:
startUrls(Upwork search URL with skill filters),pseudoUrls,maxCrawledPages
Output fields
Step 1: title, description, budget, clientJobsPosted, clientHireRate, postedAt, url
Gotcha
No dedicated Upwork Actor exists in Apify Store - verify with apify actors search "upwork" --user-agent apify-agent-skills/apify-ultimate-scraper for community options before defaulting to apify/playwright-scraper. Upwork pages are JS-heavy so Playwright is required over basic HTTP scraping. For high-frequency monitoring (every 15 min), store seen job URLs to avoid re-processing duplicates.
GitHub contributor discovery
When: User wants to find developers who contribute to specific open-source projects.
Pipeline
Get contributors ->
janbuchar/github-contributors-scraperKey input:
repoUrls
Output fields
Step 1: username, contributions, profileUrl, avatarUrl
Requirements and compatibility
Written for: Claude Code
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Names Claude Code tools, Needs Node.js
Security
What our scanner noticed· Low risk
- Instructions that use the network
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Published by
- Apify
- Publisher
- Apify (Official)
- Source
- apify/agent-skills · skills/apify-ultimate-scraper · commit f22557f
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (written by AutoGineer)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by Apify or Apify.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download apify-ultimate-scraper.zip