crawl은(는) 무엇을 하나요?
모든 웹사이트를 크롤링하여 로컬 마크다운 파일로 저장합니다. 문서, 지식 베이스, 웹 콘텐츠를 오프라인 접근 또는 분석을 위해 다운로드해야 할 때 사용하세요. 코드가 필요 없으며 URL만 제공하면 됩니다.
모든 웹사이트를 크롤링하여 로컬 마크다운 파일로 저장합니다. 문서, 지식 베이스, 웹 콘텐츠를 오프라인 접근 또는 분석을 위해 다운로드해야 할 때 사용하세요. 코드가 필요 없으며 URL만 제공하면 됩니다.
tavily-ai/crawl은 웹사이트의 콘텐츠를 자동으로 크롤링하여 로컬 마크다운 파일로 저장하는 AI 에이전트 스킬입니다. 이 스킬은 Claude Code, Cursor, Codex와 같은 AI 에이전트 플랫폼에서 사용할 수 있으며, 개발자가 문서, 지식 베이스, 블로그 게시물 등 웹 콘텐츠를 구조화된 형식으로 오프라인에 저장하거나 분석 목적으로 다운로드해야 할 때 유용합니다. 사용자는 복잡한 코딩 없이 단순히 대상 URL만 제공하면 되며, 스킬이 자동으로 웹사이트를 탐색하고 페이지를 추출하여 로컬 파일 시스템에 마크다운 형식으로 저장합니다. 이 과정에서 링크 구조, 이미지 참조, 코드 블록 등 원본 서식의 중요한 요소를 보존하며, 필요한 경우 특정 페이지 깊이나 범위를 지정할 수 있어 대규모 문서 세트를 효율적으로 수집할 수 있습니다. 결과물은 마크다운 편집기나 버전 관리 시스템과 쉽게 통합되어 팀 협업 및 지식 관리에 활용될 수 있습니다.
npx skills add https://github.com/tavily-ai/skills/tree/main/skills/crawlInstalled? Explore more 연구 & 데이터 분석 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
모든 웹사이트를 크롤링하여 로컬 마크다운 파일로 저장합니다. 문서, 지식 베이스, 웹 콘텐츠를 오프라인 접근 또는 분석을 위해 다운로드해야 할 때 사용하세요. 코드가 필요 없으며 URL만 제공하면 됩니다.
This repo contains 11 individual skills — each has its own dedicated page.
Extract content from specific URLs using Tavily's extraction API. Returns clean markdown/text from web pages. Use when you have specific URLs and need their content without writing code.
Comprehensive research grounded in web data with explicit citations. Use when you need multi-source synthesis—comparisons, current events, market analysis, detailed reports.
Search the web using Tavily's LLM-optimized search API. Returns relevant results with content snippets, scores, and metadata. Use when you need to find web content on any topic without writing code.
Build production-ready Tavily integrations with best practices baked in. Reference documentation for developers using coding assistants (Claude Code, Cursor, etc.) to implement web search, content extraction, crawling, and research in agentic workflows, RAG systems, or autonomous agents.
Web search, content extraction, crawling, and deep research via the Tavily CLI. Use this skill whenever the user wants to search the web, find articles, research a topic, look something up online, extract content from a URL, grab text from a webpage, crawl documentation, download a site's pages, discover URLs on a domain, or conduct in-depth research with citations. Also use when they say "fetch this page", "pull the content from", "get the page at https://", "find me articles about", or reference extracting data from external websites. This provides LLM-optimized web search, content extraction, site crawling, URL discovery, and AI-powered deep research — capabilities beyond what agents can do natively. Do NOT trigger for local file operations, git commands, deployments, or code editing tasks.
Crawl websites and extract content from multiple pages via the Tavily CLI. Use this skill when the user wants to crawl a site, download documentation, extract an entire docs section, bulk-extract pages, save a site as local markdown files, or says "crawl", "get all the pages", "download the docs", "extract everything under /docs", "bulk extract", or needs content from many pages on the same domain. Supports depth/breadth control, path filtering, semantic instructions, and saving each page as a local markdown file.
Programmatic web search with context isolation. Use this skill for any research task where you need to search the web, filter results, and extract specific information — without polluting your context window with raw HTML and boilerplate. This is the default skill for web research. Triggered by "search for", "look up", "find", "research", "what's the latest on", or any query that requires current web information. Also use when asked to "search and filter", "find the important parts", or "extract the key details" — any case where the user wants curated, noise-free content.
Extract clean markdown or text content from specific URLs via the Tavily CLI. Use this skill when the user has one or more URLs and wants their content, says "extract", "grab the content from", "pull the text from", "get the page at", "read this webpage", or needs clean text from web pages. Handles JavaScript-rendered pages, returns LLM-optimized markdown, and supports query-focused chunking for targeted extraction. Can process up to 20 URLs in a single call.
Discover and list all URLs on a website without extracting content, via the Tavily CLI. Use this skill when the user wants to find a specific page on a large site, list all URLs, see the site structure, find where something is on a domain, or says "map the site", "find the URL for", "what pages are on", "list all pages", or "site structure". Faster than crawling — returns URLs only. Essential when you know the site but not the exact page. Combine with extract for targeted content retrieval.
Conduct comprehensive AI-powered research with citations via the Tavily CLI. Use this skill when the user wants deep research, a detailed report, a comparison, market analysis, literature review, or says "research", "investigate", "analyze in depth", "compare X vs Y", "what does the market look like for", or needs multi-source synthesis with explicit citations. Returns a structured report grounded in web sources. Takes 30-120 seconds. For quick fact-finding, use tavily-search instead.
Search the web with LLM-optimized results via the Tavily CLI. Use this skill when the user wants to search the web, find articles, look up information, get recent news, discover sources, or says "search for", "find me", "look up", "what's the latest on", "find articles about", or needs current information from the internet. Returns relevant results with content snippets, relevance scores, and metadata — optimized for LLM consumption. Supports domain filtering, time ranges, and multiple search depths.
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.