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tavily-ai/research

ウェブデータに基づく包括的な調査と明示的な引用を提供します。比較、時事、市場分析、詳細なレポートなど、複数ソースの統合が必要な場合に使用します。

research とは?

このスキルは、Tavily AIを活用して、ウェブ上の複数ソースから情報を収集・統合し、信頼性の高い調査結果を提供します。開発者やAIエージェントユーザーは、このスキルを使用することで、最新の時事、市場分析、製品比較、詳細なレポートなどを効率的に生成できます。各回答には明示的な引用が含まれており、情報の出所を確認できるため、事実に基づいた意思決定が可能です。このスキルは、Claude CodeやCursorなどのAIエージェントプラットフォームと互換性があり、自然言語のクエリを通じて複雑な調査タスクを自動化します。

対応~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/tavily-ai/skills/tree/main/skills/research

Installed? 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 →

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このエージェントスキルを事前に読み込んだ状態で新しいチャットを開きます。

ドキュメント

research は何をしますか?

ウェブデータに基づく包括的な調査と明示的な引用を提供します。比較、時事、市場分析、詳細なレポートなど、複数ソースの統合が必要な場合に使用します。

概要

このスキルは、Tavily AIの検索・集約機能を利用して、ユーザーのクエリに関連する複数のウェブソースから情報を収集します。結果は要約され、各主張に対して引用が付与されるため、情報の検証が容易です。

主な機能

  • マルチソース統合: 複数のウェブサイトから情報を取得し、統合された回答を生成。
  • 明示的な引用: すべての情報にソースURLを含む引用が付き、信頼性を担保。
  • 多様なユースケース: 時事ニュース、市場分析、製品比較、技術調査などに対応。
  • カスタマイズ可能: 検索深度、ソース数、対象ドメインなどのパラメータを調整可能。

プラットフォーム

  • Claude Code
  • Cursor
  • その他のAIエージェント(OpenAI互換API対応)

使用例

「最新のAI業界動向を調査し、主要企業の戦略を比較して」
「2024年の電気自動車市場の分析レポートを作成し、テスラとBYDの比較を含めて」

設定

環境変数 TAVILY_API_KEY を設定してください。APIキーは Tavily AI ダッシュボード から取得できます。

export TAVILY_API_KEY=your_api_key_here

ライセンス

MIT

Individual skills in this repo

This repo contains 11 individual skills — each has its own dedicated page.

tavily-ai/crawl

Crawl any website and save pages as local markdown files. Use when you need to download documentation, knowledge bases, or web content for offline access or analysis. No code required - just provide a URL.

tavily-ai/extract

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.

tavily-ai/search

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.

tavily-ai/tavily-best-practices

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.

tavily-ai/tavily-cli

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.

tavily-ai/tavily-crawl

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.

tavily-ai/tavily-dynamic-search

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.

tavily-ai/tavily-extract

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.

tavily-ai/tavily-map

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.

tavily-ai/tavily-research

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.

tavily-ai/tavily-search

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.

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