Token导航 LogoToken导航

Agent Skill · 研究检索

tavily(Tavily 网络搜索)

tavily 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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。

tavily 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证为 MIT,暂无第三方扫描结果,按安装量在研究检索类的 73,675 个 Skill 里排第 71,089。

总安装 196周安装 8GitHub Stars 公开资料未说明下载 63核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

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/clawdbot/skills
仓库路径:skills/tavily
安装命令:
npx skills add clawdbot/skills --skill "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 npx skills 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。

AgentSkills.tonpx skills
npx skills add clawdbot/skills --skill "tavily"

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

tavily 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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。它主要用于研究检索类任务,可结合来源仓库、安装命令和原始 README 继续核验具体用法。

通过 npx skills add clawdbot/skills --skill "tavily" 命令安装,支持主流 AI 宿主平台。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。tavily 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/tavily

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add clawdbot/skills --skill "tavily";命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

tavily 怎么安装?

在终端执行 npx skills add clawdbot/skills --skill "tavily"。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

tavily 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

tavily 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

tavily 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

tavily 用的人多吗?

公开数据是累计安装 196 次,近一周安装 8 次,下载 63 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

tavily 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 要求有安全扫描结论才肯安装的团队。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
tavily

Tavily 网络搜索 · 本页

196—调用外部服务MIT未收录

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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

平台分布

mcpjam

26.78%
按下载量换算17

Claude Code

23.26%
按下载量换算15

kilo

18.1%
按下载量换算11

junie

11.92%
按下载量换算8

windsurf

7.71%
按下载量换算5

zencoder

3.5%
按下载量换算2

安全审计

暂无安全审计结果可展示。

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills