firecrawl-shop 是做什麼的？
使用 Firecrawl 在網路上研究產品，並產出購物推薦或可加入購物車的摘要。當使用者想要比較產品、尋找最佳選項、評估評論、考慮預算/偏好，或使用已儲存的瀏覽器工作階段購物時使用。
使用 Firecrawl 在網路上研究產品，並產出購物推薦或可加入購物車的摘要。當使用者想要比較產品、尋找最佳選項、評估評論、考慮預算/偏好，或使用已儲存的瀏覽器工作階段購物時使用。
firecrawl/firecrawl-shop 是一個專為購物研究與推薦設計的 AI 代理技能，核心能力是透過 Firecrawl 爬蟲技術，從多個電子商務網站（如 Amazon、蝦皮、PChome 等）獲取產品資訊。它能自動比較不同產品的價格、規格、評價和庫存狀態，並根據使用者設定的預算與偏好（例如品牌、保固、運送時間）產出個性化的購物建議或可直接加入購物車的產品清單。此技能支援任何能執行爬蟲任務的 AI 代理平台，例如 Claude Code、Coder 或自訂工具；工作流程包含初始化爬蟲任務、定義目標網站與關鍵字、執行次數有限的深度爬取、以及輸出結構化摘要。使用者可選擇讓代理使用已儲存的瀏覽器 Session 以繞過登入或驗證限制，從而獲得更準確的即時價格與庫存資料。總之，這項技能大幅簡化了跨平台產品研究與購物決策流程，特別適合需要快速比較多樣商品、尋找最划算選擇或限制預算的使用者。
npx skills add https://github.com/firecrawl/firecrawl-workflows/tree/main/skills/firecrawl-shopInstalled? Explore more 研究與資料分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
使用 Firecrawl 在網路上研究產品，並產出購物推薦或可加入購物車的摘要。當使用者想要比較產品、尋找最佳選項、評估評論、考慮預算/偏好，或使用已儲存的瀏覽器工作階段購物時使用。
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.