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tavilyTavily 网络搜索

Agent Skill

tavily 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

1,180,499

周安装

48,223

GitHub Stars

30

下载量

381,926
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:tavily(Tavily 网络搜索)
来源仓库:https://github.com/bert-builder/tavily
安装命令:
openclaw skills install tavily
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install tavily

简介

使用 Tavily Search API 进行 AI 优化的网络搜索。当您需要全面的网络研究、时事查找、特定领域的搜索或人工智能生成的答案摘要时使用。 Tavily 针对 LLM 的使用进行了优化,具有清晰的结构化结果、答案生成和原始内容提取。最适合研究任务、新闻查询、事实检查和收集权威来源。

SKILL.md

name
tavily
description
AI-optimized web search using Tavily Search API. Use when you need comprehensive web research, current events lookup, domain-specific search, or AI-generated answer summaries. Tavily is optimized for LLM consumption with clean structured results, answer generation, and raw content extraction. Best for research tasks, news queries, fact-checking, and gathering authoritative sources.

Tavily AI Search

Overview

Tavily is a search engine specifically optimized for Large Language Models and AI applications. Unlike traditional search APIs, Tavily provides AI-ready results with optional answer generation, clean content extraction, and domain filtering capabilities.

Key capabilities:

  • AI-generated answer summaries from search results
  • Clean, structured results optimized for LLM processing
  • Fast (basic) and comprehensive (advanced) search modes
  • Domain filtering (include/exclude specific sources)
  • News-focused search for current events
  • Image search with relevant visual content
  • Raw content extraction for deeper analysis

Architecture

graph TB
    A[User Query] --> B{Search Mode}
    B -->|basic| C[Fast Search<br/>1-2s response]
    B -->|advanced| D[Comprehensive Search<br/>5-10s response]
    
    C --> E[Tavily API]
    D --> E
    
    E --> F{Topic Filter}
    F -->|general| G[Broad Web Search]
    F -->|news| H[News Sources<br/>Last 7 days]
    
    G --> I[Domain Filtering]
    H --> I
    
    I --> J{Include Domains?}
    J -->|yes| K[Filter to Specific Domains]
    J -->|no| L{Exclude Domains?}
    K --> M[Search Results]
    L -->|yes| N[Remove Unwanted Domains]
    L -->|no| M
    N --> M
    
    M --> O{Response Options}
    O --> P[AI Answer<br/>Summary]
    O --> Q[Structured Results<br/>Title, URL, Content, Score]
    O --> R[Images<br/>if requested]
    O --> S[Raw HTML Content<br/>if requested]
    
    P --> T[Return to Agent]
    Q --> T
    R --> T
    S --> T
    
    style E fill:#4A90E2
    style P fill:#7ED321
    style Q fill:#7ED321
    style R fill:#F5A623
    style S fill:#F5A623

Quick Start

Basic Search

# Simple query with AI answer
scripts/tavily_search.py "What is quantum computing?"

# Multiple results
scripts/tavily_search.py "Python best practices" --max-results 10

Advanced Search

# Comprehensive research mode
scripts/tavily_search.py "Climate change solutions" --depth advanced

# News-focused search
scripts/tavily_search.py "AI developments 2026" --topic news

Domain Filtering

# Search only trusted domains
scripts/tavily_search.py "Python tutorials" \
  --include-domains python.org docs.python.org realpython.com

# Exclude low-quality sources
scripts/tavily_search.py "How to code" \
  --exclude-domains w3schools.com geeksforgeeks.org

With Images

# Include relevant images
scripts/tavily_search.py "Eiffel Tower architecture" --images

Search Modes

Basic vs Advanced

ModeSpeedCoverageUse Case
basic1-2sGoodQuick facts, simple queries
advanced5-10sExcellentResearch, complex topics, comprehensive analysis

Decision tree:

  1. Need a quick fact or definition? → Use basic
  2. Researching a complex topic? → Use advanced
  3. Need multiple perspectives? → Use advanced
  4. Time-sensitive query? → Use basic

General vs News

TopicTime RangeSourcesUse Case
generalAll timeBroad webEvergreen content, tutorials, documentation
newsLast 7 daysNews sitesCurrent events, recent developments, breaking news

Decision tree:

  1. Query contains "latest", "recent", "current", "today"? → Use news
  2. Looking for historical or evergreen content? → Use general
  3. Need up-to-date information? → Use news

API Key Setup

Option 1: Clawdbot Config (Recommended)

Add to your Clawdbot config:

{
  "skills": {
    "entries": {
      "tavily": {
        "enabled": true,
        "apiKey": "tvly-YOUR_API_KEY_HERE"
      }
    }
  }
}

Access in scripts via Clawdbot's config system.

Option 2: Environment Variable

export TAVILY_API_KEY="tvly-YOUR_API_KEY_HERE"

Add to ~/.clawdbot/.env or your shell profile.

Getting an API Key

  1. Visit https://tavily.com
  2. Sign up for an account
  3. Navigate to your dashboard
  4. Generate an API key (starts with tvly-)
  5. Note your plan's rate limits and credit allocation

Common Use Cases

1. Research & Fact-Finding

# Comprehensive research with answer
scripts/tavily_search.py "Explain quantum entanglement" --depth advanced

# Multiple authoritative sources
scripts/tavily_search.py "Best practices for REST API design" \
  --max-results 10 \
  --include-domains github.com microsoft.com google.com

2. Current Events

# Latest news
scripts/tavily_search.py "AI policy updates" --topic news

# Recent developments in a field
scripts/tavily_search.py "quantum computing breakthroughs" \
  --topic news \
  --depth advanced

3. Domain-Specific Research

# Academic sources only
scripts/tavily_search.py "machine learning algorithms" \
  --include-domains arxiv.org scholar.google.com ieee.org

# Technical documentation
scripts/tavily_search.py "React hooks guide" \
  --include-domains react.dev

4. Visual Research

# Gather visual references
scripts/tavily_search.py "modern web design trends" \
  --images \
  --max-results 10

5. Content Extraction

# Get raw HTML content for deeper analysis
scripts/tavily_search.py "Python async/await" \
  --raw-content \
  --max-results 5

Response Handling

AI Answer

The AI-generated answer provides a concise summary synthesized from search results:

{
  "answer": "Quantum computing is a type of computing that uses quantum-mechanical phenomena..."
}

Use when:

  • Need a quick summary
  • Want synthesized information from multiple sources
  • Looking for a direct answer to a question

Skip when (--no-answer):

  • Only need source URLs
  • Want to form your own synthesis
  • Conserving API credits

Structured Results

Each result includes:

  • title: Page title
  • url: Source URL
  • content: Extracted text snippet
  • score: Relevance score (0-1)
  • raw_content: Full HTML (if --raw-content enabled)

Images

When --images is enabled, returns URLs of relevant images found during search.

Best Practices

1. Choose the Right Search Depth

  • Start with basic for most queries (faster, cheaper)
  • Escalate to advanced only when:

- Initial results are insufficient - Topic is complex or nuanced - Need comprehensive coverage

2. Use Domain Filtering Strategically

Include domains for:

  • Academic research (.edu domains)
  • Official documentation (official project sites)
  • Trusted news sources
  • Known authoritative sources

Exclude domains for:

  • Known low-quality content farms
  • Irrelevant content types (Pinterest for non-visual queries)
  • Sites with paywalls or access restrictions

3. Optimize for Cost

  • Use basic depth as default
  • Limit max_results to what you'll actually use
  • Disable include_raw_content unless needed
  • Cache results locally for repeated queries

4. Handle Errors Gracefully

The script provides helpful error messages:

# Missing API key
Error: Tavily API key required
Setup: Set TAVILY_API_KEY environment variable or pass --api-key

# Package not installed
Error: tavily-python package not installed
To install: pip install tavily-python

Integration Patterns

Programmatic Usage

from tavily_search import search

result = search(
    query="What is machine learning?",
    api_key="tvly-...",
    search_depth="advanced",
    max_results=10
)

if result.get("success"):
    print(result["answer"])
    for item in result["results"]:
        print(f"{item['title']}: {item['url']}")

JSON Output for Parsing

scripts/tavily_search.py "Python tutorials" --json > results.json

Chaining with Other Tools

# Search and extract content
scripts/tavily_search.py "React documentation" --json | \
  jq -r '.results[].url' | \
  xargs -I {} curl -s {}

Comparison with Other Search APIs

vs Brave Search:

  • ✅ AI answer generation
  • ✅ Raw content extraction
  • ✅ Better domain filtering
  • ❌ Slower than Brave
  • ❌ Costs credits

vs Perplexity:

  • ✅ More control over sources
  • ✅ Raw content available
  • ✅ Dedicated news mode
  • ≈ Similar answer quality
  • ≈ Similar speed

vs Google Custom Search:

  • ✅ LLM-optimized results
  • ✅ Answer generation
  • ✅ Simpler API
  • ❌ Smaller index
  • ≈ Similar cost structure

Troubleshooting

Script Won't Run

# Make executable
chmod +x scripts/tavily_search.py

# Check Python version (requires 3.6+)
python3 --version

# Install dependencies
pip install tavily-python

API Key Issues

# Verify API key format (should start with tvly-)
echo $TAVILY_API_KEY

# Test with explicit key
scripts/tavily_search.py "test" --api-key "tvly-..."

Rate Limit Errors

  • Check your plan's credit allocation at https://tavily.com
  • Reduce max_results to conserve credits
  • Use basic depth instead of advanced
  • Implement local caching for repeated queries

Resources

See api-reference.md for:

  • Complete API parameter documentation
  • Response format specifications
  • Error handling details
  • Cost and rate limit information
  • Advanced usage examples

Dependencies

  • Python 3.6+
  • tavily-python package (install: pip install tavily-python)
  • Valid Tavily API key

Credits & Attribution

  • Tavily API: https://tavily.com
  • Python SDK: https://github.com/tavily-ai/tavily-python
  • Documentation: https://docs.tavily.com

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

82.68%
按下载量换算315,776

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

未展示

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

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来源信息

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