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Tavily Search Pro

Tavily AI search platform with 5 modes: Search (web/news/finance), Extract (URL content), Crawl (website crawling), Map (sitemap discovery), and Research (deep research with citations). Use for: web search with LLM answers, content extraction, site crawling, deep research.
Tavily AI 搜索平台,提供 5 种模式:搜索(网页/新闻/金融)、提取(URL 内容)、爬取(网站爬取)、映射(站点地图发现)和研究(深度研究,含引用)。用途:LLM 回答的网页搜索、内容提取、网站爬取、深度研究。
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概述

Tavily Search 🔎

AI-powered web search platform with 5 modes: Search, Extract, Crawl, Map, and Research.

Requirements

  • TAVILY_API_KEY environment variable

Configuration

Env VariableDefaultDescription
---------
TAVILY_API_KEYRequired. Tavily API key

Set in OpenClaw config:

{
  "env": {
    "TAVILY_API_KEY": "tvly-..."
  }
}

Script Location

python3 skills/tavily/lib/tavily_search.py <command> "query" [options]

Commands

search — Web Search (Default)

General-purpose web search with optional LLM-synthesized answer.

python3 lib/tavily_search.py search "query" [options]

Examples:

# Basic search
python3 lib/tavily_search.py search "latest AI news"

# With LLM answer
python3 lib/tavily_search.py search "what is quantum computing" --answer

# Advanced depth (better results, 2 credits)
python3 lib/tavily_search.py search "climate change solutions" --depth advanced

# Time-filtered
python3 lib/tavily_search.py search "OpenAI announcements" --time week

# Domain filtering
python3 lib/tavily_search.py search "machine learning" --include-domains arxiv.org,nature.com

# Country boost
python3 lib/tavily_search.py search "tech startups" --country US

# With raw content and images
python3 lib/tavily_search.py search "solar energy" --raw --images -n 10

# JSON output
python3 lib/tavily_search.py search "bitcoin price" --json

Output format (text):

Answer: <LLM-synthesized answer if --answer>

Results:
  1. Result Title
     https://example.com/article
     Content snippet from the page...

  2. Another Result
     https://example.com/other
     Another snippet...

news — News Search

Search optimized for news articles. Sets topic=news.

python3 lib/tavily_search.py news "query" [options]

Examples:

python3 lib/tavily_search.py news "AI regulation"
python3 lib/tavily_search.py news "Israel tech" --time day --answer
python3 lib/tavily_search.py news "stock market" --time week -n 10

finance — Finance Search

Search optimized for financial data and news. Sets topic=finance.

python3 lib/tavily_search.py finance "query" [options]

Examples:

python3 lib/tavily_search.py finance "NVIDIA stock analysis"
python3 lib/tavily_search.py finance "cryptocurrency market trends" --time month
python3 lib/tavily_search.py finance "S&P 500 forecast 2026" --answer

extract — Extract Content from URLs

Extract readable content from one or more URLs.

python3 lib/tavily_search.py extract URL [URL...] [options]

Parameters:

  • urls: One or more URLs to extract (positional args)
  • --depth basic|advanced: Extraction depth
  • --format markdown|text: Output format (default: markdown)
  • --query "text": Rerank extracted chunks by relevance to query

Examples:

# Extract single URL
python3 lib/tavily_search.py extract "https://example.com/article"

# Extract multiple URLs
python3 lib/tavily_search.py extract "https://url1.com" "https://url2.com"

# Advanced extraction with relevance reranking
python3 lib/tavily_search.py extract "https://arxiv.org/paper" --depth advanced --query "transformer architecture"

# Text format output
python3 lib/tavily_search.py extract "https://example.com" --format text

Output format:

URL: https://example.com/article
─────────────────────────────────
<Extracted content in markdown/text>

URL: https://another.com/page
─────────────────────────────────
<Extracted content>

crawl — Crawl a Website

Crawl a website starting from a root URL, following links.

python3 lib/tavily_search.py crawl URL [options]

Parameters:

  • url: Root URL to start crawling
  • --depth basic|advanced: Crawl depth
  • --max-depth N: Maximum link depth to follow (default: 2)
  • --max-breadth N: Maximum pages per depth level (default: 10)
  • --limit N: Maximum total pages (default: 10)
  • --instructions "text": Natural language crawl instructions
  • --select-paths p1,p2: Only crawl these path patterns
  • --exclude-paths p1,p2: Skip these path patterns
  • --format markdown|text: Output format

Examples:

# Basic crawl
python3 lib/tavily_search.py crawl "https://docs.example.com"

# Focused crawl with instructions
python3 lib/tavily_search.py crawl "https://docs.python.org" --instructions "Find all asyncio documentation" --limit 20

# Crawl specific paths only
python3 lib/tavily_search.py crawl "https://example.com" --select-paths "/blog,/docs" --max-depth 3

Output format:

Crawled 5 pages from https://docs.example.com

Page 1: https://docs.example.com/intro
─────────────────────────────────
<Content>

Page 2: https://docs.example.com/guide
─────────────────────────────────
<Content>

map — Sitemap Discovery

Discover all URLs on a website (sitemap).

python3 lib/tavily_search.py map URL [options]

Parameters:

  • url: Root URL to map
  • --max-depth N: Depth to follow (default: 2)
  • --max-breadth N: Breadth per level (default: 20)
  • --limit N: Maximum URLs (default: 50)

Examples:

# Map a site
python3 lib/tavily_search.py map "https://example.com"

# Deep map
python3 lib/tavily_search.py map "https://docs.python.org" --max-depth 3 --limit 100

Output format:

Sitemap for https://example.com (42 URLs found):

  1. https://example.com/
  2. https://example.com/about
  3. https://example.com/blog
  ...

research — Deep Research

Comprehensive AI-powered research on a topic with citations.

python3 lib/tavily_search.py research "query" [options]

Parameters:

  • query: Research question
  • --model mini|pro|auto: Research model (default: auto)
  • mini: Faster, cheaper
  • pro: More thorough
  • auto: Let Tavily decide
  • --json: JSON output (supports structured output schema)

Examples:

# Basic research
python3 lib/tavily_search.py research "Impact of AI on healthcare in 2026"

# Pro model for thorough research
python3 lib/tavily_search.py research "Comparison of quantum computing approaches" --model pro

# JSON output
python3 lib/tavily_search.py research "Electric vehicle market analysis" --json

Output format:

Research: Impact of AI on healthcare in 2026

<Comprehensive research report with citations>

Sources:
  [1] https://source1.com
  [2] https://source2.com
  ...

Options Reference

OptionApplies ToDescriptionDefault
------------
`--depth basic\advanced`search, news, finance, extractSearch/extraction depthbasic
`--time day\week\month\year`search, news, financeTime range filternone
-n NUMsearch, news, financeMax results (0-20)5
--answersearch, news, financeInclude LLM answeroff
--rawsearch, news, financeInclude raw page contentoff
--imagessearch, news, financeInclude image URLsoff
--include-domains d1,d2search, news, financeOnly these domainsnone
--exclude-domains d1,d2search, news, financeExclude these domainsnone
--country XXsearch, news, financeBoost country resultsnone
--jsonallStructured JSON outputoff
`--format markdown\text`extract, crawlContent formatmarkdown
--query "text"extractRelevance reranking querynone
`--model mini\pro\auto`researchResearch modelauto
--max-depth Ncrawl, mapMax link depth2
--max-breadth Ncrawl, mapMax pages per level10/20
--limit Ncrawl, mapMax total pages/URLs10/50
--instructions "text"crawlNatural language instructionsnone
--select-paths p1,p2crawlInclude path patternsnone
--exclude-paths p1,p2crawlExclude path patternsnone

Error Handling

  • Missing API key: Clear error message with setup instructions.
  • 401 Unauthorized: Invalid API key.
  • 429 Rate Limit: Rate limit exceeded, try again later.
  • Network errors: Descriptive error with cause.
  • No results: Clean "No results found." message.
  • Timeout: 30-second timeout on all HTTP requests.

Credits & Pricing

APIBasicAdvanced
---------
Search1 credit2 credits
Extract1 credit/URL2 credits/URL
Crawl1 credit/page2 credits/page
Map1 credit1 credit
ResearchVaries by model-

Install

bash skills/tavily/install.sh

版本历史

共 1 个版本

  • v1.0.0 当前
    2026-03-28 09:50 安全 安全

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腾讯云安全 (Sanbu)

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