firecrawl-shop은(는) 무엇을 하나요?
Firecrawl을 사용하여 웹 전반에서 제품을 조사하고, 쇼핑 추천 또는 장바구니에 바로 담을 수 있는 요약을 생성합니다. 사용자가 제품을 비교하고, 최적의 옵션을 찾고, 리뷰를 평가하고, 예산/선호도를 고려하거나, 저장된 브라우저 세션으로 쇼핑할 때 사용하세요.
Firecrawl을 사용하여 웹 전반에서 제품을 조사하고, 쇼핑 추천 또는 장바구니에 바로 담을 수 있는 요약을 생성합니다. 사용자가 제품을 비교하고, 최적의 옵션을 찾고, 리뷰를 평가하고, 예산/선호도를 고려하거나, 저장된 브라우저 세션으로 쇼핑할 때 사용하세요.
이 스킬은 Firecrawl을 활용하여 사용자의 제품 조사 및 쇼핑 의사 결정 과정을 자동화합니다. 사용자가 '최고의 노트북 비교해줘' 또는 '예산 내에서 최고의 커피 머신 추천해줘' 같은 요청을 하면, Firecrawl이 여러 웹사이트를 탐색하여 제품 정보, 가격, 리뷰를 수집하고 이를 바탕으로 추천 목록이나 장바구니 요약을 생성합니다. 주로 Claude Code, Cursor, Codex와 같은 AI 에이전트 플랫폼과 함께 사용되며, Firecrawl의 웹 스크래핑 기능을 통해 실시간 데이터를 수집합니다. 이 스킬은 사용자의 예산, 선호도, 저장된 브라우저 세션 정보를 존중하여 개인화된 쇼핑 경험을 제공하며, 최종적으로 구매 결정을 돕기 위한 구조화된 요약을 생성합니다. 개발자나 고급 사용자는 Firecrawl API 키와 옵션을 설정하여 검색 범위와 깊이를 제어할 수 있습니다.
npx skills add https://github.com/firecrawl/firecrawl-workflows/tree/main/skills/firecrawl-shopInstalled? Explore more 연구 & 데이터 분석 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
Firecrawl을 사용하여 웹 전반에서 제품을 조사하고, 쇼핑 추천 또는 장바구니에 바로 담을 수 있는 요약을 생성합니다. 사용자가 제품을 비교하고, 최적의 옵션을 찾고, 리뷰를 평가하고, 예산/선호도를 고려하거나, 저장된 브라우저 세션으로 쇼핑할 때 사용하세요.
This repo contains 15 individual skills — each has its own dedicated page.
Extract structured company lists from directories with Firecrawl. Use for scraping YC, Crunchbase, Product Hunt, G2, startup directories, category directories, or custom company databases into JSON, CSV, CRM-ready lists, or research tables.
Monitor competitor pricing, features, changelogs, dashboards, and product changes with Firecrawl. Use for recurring competitive intelligence, pricing tier extraction, feature change tracking, or structured competitor alerts.
Pull metrics from analytics dashboards and internal web tools with Firecrawl browser. Use when the user needs dashboard reporting, cross-platform metric summaries, authenticated analytics extraction, date-range reports, or structured metrics from web dashboards.
Run multi-source deep research with Firecrawl. Use when the user asks to research a topic, compare perspectives, produce a sourced briefing, investigate a technical or market question, or synthesize web evidence across many sources.
Walk through a product's key flows with Firecrawl browser and produce a structured UX/product walkthrough. Use for signup, onboarding, pricing, docs, dashboard, product demo prep, UX teardown, and first-run experience analysis.
Build a knowledge base from web content with Firecrawl. Use for local reference docs, RAG-ready chunks, fine-tuning datasets, documentation mirrors, topic corpora, or LLM-ready markdown organized from web sources.
Ingest public or authenticated knowledge bases and docs portals with Firecrawl browser. Use for JS-heavy docs, login-gated portals, paginated help centers, support knowledge bases, or structured JSON/markdown extraction from documentation sites.
Generate structured lead lists from prospect databases and web directories with Firecrawl browser. Use for finding prospects by role, company type, industry, stage, location, technologies, or other criteria and exporting CRM-ready JSON or CSV.
Produce pre-meeting lead intelligence briefs with Firecrawl. Use when the user needs company research, person research, recent news, talking points, pain points, or outreach preparation before a sales call, partnership meeting, investor conversation, or customer interview.
Extract market, financial, earnings, industry, and company metrics with Firecrawl. Use when the user asks for market research, industry trends, public company data, financial comparisons, earnings research, or structured market reports.
QA test a live website with Firecrawl browser and scrape evidence. Use when the user wants exploratory QA, form testing, navigation/link checks, responsive checks, performance observations, bug reports, or a pre-launch quality review.
Find and synthesize research papers, whitepapers, PDFs, technical reports, and academic sources with Firecrawl. Use when the user wants a literature review, paper summary, research landscape, or sourced synthesis from PDFs and scholarly/industry publications.
Audit a website's SEO with Firecrawl. Use when the user asks for an SEO audit, metadata and heading review, sitemap/site-structure analysis, keyword opportunities, competitor SERP comparison, or prioritized search optimization recommendations.
Extract any website's design system into an agent-ready DESIGN.md using Firecrawl scrape evidence. Use when the user wants colors, fonts, spacing, components, layout patterns, or brand/UI guidance from a website so AI agents can create new websites, clone a look, or build pages inspired by that design.
Run outcome-focused Firecrawl workflows that produce deliverables such as research reports, SEO audits, QA reports, lead lists, knowledge bases, website design systems, and other structured web-data artifacts. Use when the user wants Firecrawl to complete a business, marketing, product, or creative workflow rather than merely scrape a page or integrate API calls into code.
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.