apify-ecommerce は何をしますか？
Amazon、Walmart、eBay、IKEAなど50以上のマーケットプレイスから、価格情報、カスタマーレビュー、出品者情報をスクレイピングします。価格監視、競合追跡、レビュー分析、商品調査、出品者検索に活用できます。
このスキルは、ユーザーが以下のようなリクエストを行った場合に使用します。
- 価格の監視
- 競合他社の追跡
- レビューの分析
- 商品の調査
- 出品者の検索
Amazon、Walmart、eBay、IKEAなど50以上のマーケットプレイスから、価格情報、カスタマーレビュー、出品者情報をスクレイピングします。価格監視、競合追跡、レビュー分析、商品調査、出品者検索に活用できます。
このスキルは、ApifyのEコマースデータスクレイピング機能を提供し、Amazon、Walmart、eBay、IKEAをはじめとする50以上の主要なオンラインマーケットプレイスから、価格情報、カスタマーレビュー、出品者情報を自動的に収集します。ユーザーが価格モニタリング、競合他社の追跡、レビュー分析、商品調査、出品者検索を依頼した際に特に有用です。このスキルは、AIエージェント（Claude Code、Cursor、Codexなど）と統合して動作し、Apifyのデータ抽出機能を活用することで、大規模なEコマースデータの収集と分析を効率的に行います。具体的には、ユーザーのクエリに基づいて適切なApifyアクターを選択し、必要なデータをスクレイピングして結果を構造化された形式で返します。ブラウザ自動化ツールやWebスクレイパーを直接操作する代わりに、自然言語での指示だけで複雑なEコマースデータ収集を実現できる点が大きな利点です。
npx skills add https://github.com/apify/agent-skills/tree/main/skills/apify-ecommerceInstalled? Explore more 研究＆データ分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
Amazon、Walmart、eBay、IKEAなど50以上のマーケットプレイスから、価格情報、カスタマーレビュー、出品者情報をスクレイピングします。価格監視、競合追跡、レビュー分析、商品調査、出品者検索に活用できます。
このスキルは、ユーザーが以下のようなリクエストを行った場合に使用します。
This repo contains 13 individual skills — each has its own dedicated page.
Develop, debug, and deploy Apify Actors - serverless cloud programs for web scraping, automation, and data processing. Use when creating new Actors, modifying existing ones, or troubleshooting Actor code.
Convert existing projects into Apify Actors - serverless cloud programs. Actorize JavaScript/TypeScript (SDK with Actor.init/exit), Python (async context manager), or any language (CLI wrapper). Use when migrating code to Apify, wrapping CLI tools as Actors, or adding Actor SDK to existing projects.
Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok.
Track reviews, ratings, sentiment, and brand mentions across Google Maps, Booking.com, TripAdvisor, Facebook, Instagram, YouTube, and TikTok. Use when user asks to monitor brand reputation, analyze reviews, track mentions, or gather customer feedback.
Analyze competitor strategies, content, pricing, ads, and market positioning across Google Maps, Booking.com, Facebook, Instagram, YouTube, and TikTok.
Track engagement metrics, measure campaign ROI, and analyze content performance across Instagram, Facebook, YouTube, and TikTok.
Generate output schemas (dataset_schema.json, output_schema.json, key_value_store_schema.json) for an Apify Actor by analyzing its source code. Use when creating or updating Actor output schemas.
Find and evaluate influencers for brand partnerships, verify authenticity, and track collaboration performance across Instagram, Facebook, YouTube, and TikTok.
Generates B2B/B2C leads by scraping Google Maps, websites, Instagram, TikTok, Facebook, LinkedIn, YouTube, and Google Search. Use when user asks to find leads, prospects, businesses, build lead lists, enrich contacts, or scrape profiles for sales outreach.
Analyze market conditions, geographic opportunities, pricing, consumer behavior, and product validation across Google Maps, Facebook, Instagram, Booking.com, and TripAdvisor.
Integrate Apify into an existing JavaScript/TypeScript or Python application using the apify-client package. Use when adding web scraping, automation, or data extraction capabilities to an existing app via the Apify API.
Discover and track emerging trends across Google Trends, Instagram, Facebook, YouTube, and TikTok to inform content strategy.
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.
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Agent skill repository discovered by 10x-chat research.
Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.