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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,权限为接触敏感数据;许可证信息还不明确,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 46,976。

总安装 753周安装 32GitHub Stars 公开资料未说明下载 264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
unknown

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/clawd-tavily
仓库路径:skills/tavily
安装命令:
npx skills add https://github.com/bert-builder/clawd-tavily --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。

skills.shnpx skills
npx skills add https://github.com/bert-builder/clawd-tavily --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。

专为 AI 应用优化的网络搜索引擎,提供清洗后的结构化搜索结果与摘要。适合需要实时信息、竞品分析或外部知识补充的智能助手场景。支持域名过滤与新闻聚焦,输出可直接用于回答或推理的内容片段。使用前需配置 API 密钥并遵守调用频率限制,避免服务中断。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 https://github.com/bert-builder/clawd-tavily --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

    它需要接触敏感数据,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 https://github.com/bert-builder/clawd-tavily --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?

权限级别是接触敏感数据。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。

tavily 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

tavily 用的人多吗?

公开数据是累计安装 753 次,近一周安装 32 次,下载 264 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?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

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。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 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

753—接触敏感数据未明确未通过

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

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

平台分布

Codex

37.15%
按下载量换算98

Claude

29.18%
按下载量换算77

Cursor

18.62%
按下载量换算49

Gemini CLI

8.5%
按下载量换算22

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

未通过

权限和风险

接触敏感数据

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

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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