firecrawl-qa 是做什麼的？
使用 Firecrawl 瀏覽器對線上網站進行 QA 測試並擷取證據。適用於使用者需要探索性 QA、表單測試、導航/連結檢查、響應式檢查、效能觀察、錯誤回報或上線前品質審查時。
使用 Firecrawl 瀏覽器對線上網站進行 QA 測試並擷取證據。適用於使用者需要探索性 QA、表單測試、導航/連結檢查、響應式檢查、效能觀察、錯誤回報或上線前品質審查時。
firecrawl/firecrawl-qa 是一個專門用於對線上網站進行品質保證（QA）測試的工具技能，它整合了 Firecrawl 瀏覽器功能，能夠自動執行探索性測試、表單驗證、導航與連結檢查、響應式設計驗證、效能觀察，並產生詳細的錯誤報告。此技能主要設計用於 AI 代理工具（如 Claude Code、Cursor 等）的環境中，開發者可以透過自然語言指令啟動測試，技能會自動操作瀏覽器進行互動，並在測試過程中擷取螢幕截圖、HTML 片段、網路請求記錄等作為證據。它的核心優勢在於能夠模擬真實使用者行為，發現功能與使用體驗上的問題，尤其是那些自動化腳本難以涵蓋的邊界案例。技能透過讀取 SKILL.md 文件中的設定，支援自訂測試案例與斷言，並能將測試結果與證據打包輸出，方便整合到 CI/CD 流程或給開發團隊進行除錯。
npx skills add https://github.com/firecrawl/firecrawl-workflows/tree/main/skills/firecrawl-qaInstalled? 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 瀏覽器對線上網站進行 QA 測試並擷取證據。適用於使用者需要探索性 QA、表單測試、導航/連結檢查、響應式檢查、效能觀察、錯誤回報或上線前品質審查時。
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.
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.
Research products across the web with Firecrawl and produce a shopping recommendation or cart-ready summary. Use when the user wants to compare products, find the best option, evaluate reviews, respect budget/preferences, or shop with a saved browser session.
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.