tavily-usage
Enables web searching and structured content extraction from URLs using the Tavily MCP tools.
Install
mkdir -p .claude/skills/tavily-usage && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/1382" && unzip -o skill.zip -d .claude/skills/tavily-usage && rm skill.zipInstalls to .claude/skills/tavily-usage
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
This skill should be used when user asks to "search the web", "fetch content from URL", "extract page content", "use Tavily search", "scrape this website", "get information from this link", or "web search for X".Key capabilities
- →Perform keyword-based web searches
- →Find relevant web pages and content
- →Gather quick answers from the web
- →Extract detailed content from specific URLs
- →Analyze page content in-depth
How it works
The skill uses Tavily Search for broad keyword-based discovery and Tavily Extract for in-depth content retrieval from specific URLs, with an automatic upgrade to advanced mode for better accuracy.
Inputs & outputs
When to use tavily-usage
- →Search for real-time information
- →Extract content from specific webpages
- →Gather data for research tasks
- →Fetch information from a provided URL
About this skill
Tavily Search and Extract
Use Tavily MCP tools for web search and content retrieval operations.
Tool Selection
Tavily Search (mcp__tavily__tavily_search)
Use for:
- Keyword-based searches across the web
- Finding relevant pages and content
- Quick answer gathering
- Multiple result discovery
Best for: Initial research, finding sources, broad queries
Tavily Extract (mcp__tavily__tavily-extract)
Use for:
- Getting detailed content from specific URLs
- Deep analysis of page content
- Structured data extraction
- Following up on search results
Best for: In-depth analysis, specific URL content, detailed information
Hook Behavior
tavily_extract_to_advanced.py hook automatically upgrades extract calls to advanced mode for better accuracy when needed.
Integration Pattern
- Use
mcp__tavily__tavily_searchfor discovery phase - Analyze results to find relevant URLs
- Use
mcp__tavily__tavily-extractfor detailed content on specific URLs - Process extracted content for user needs
Environment Variables
Tavily MCP requires:
TAVILY_API_KEY- API key from Tavily (tvly-...)
Configure in shell before using the plugin.
Cost Considerations
- Search is cheaper than extract
- Use search to filter relevant URLs first
- Only extract URLs that are likely relevant
- Cache results when possible
When not to use it
- →When the user does not have a TAVILY_API_KEY configured
- →When the user needs to perform actions beyond web search and content retrieval
- →When the user wants to extract content from irrelevant URLs
Prerequisites
Limitations
- →Search is cheaper than extract.
- →Only extract URLs that are likely relevant.
- →Caching results is recommended.
How it compares
This skill integrates two distinct tools for a two-phase approach to information gathering, separating broad discovery from deep extraction, which is more efficient than using a single tool for both.
Compared to similar skills
tavily-usage side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| tavily-usage (this skill) | 5 | 7mo | No flags | Beginner |
| exa-search | 9 | 8mo | Review | Beginner |
| startup-validator | 1 | 9mo | Review | Intermediate |
| ddgs | 0 | 3mo | Review | Beginner |
Try saying
Example prompts that trigger this skill in your AI assistant.
More by fcakyon
View all by fcakyon →You might also like
exa-search
benjaminjackson
Search the web for content matching a query with AI-powered semantic search. Use for finding relevant web pages, research papers, news articles, code repositories, or any web content by meaning rather than just keywords.
startup-validator
ailabs-393
Comprehensive startup idea validation and market analysis tool. Use when users need to evaluate a startup idea, assess market fit, analyze competition, validate problem-solution fit, or determine market positioning. Triggers include requests to "validate my startup idea", "analyze market opportunity", "check if there's demand for", "research competition for", "evaluate business idea", or "see if my idea is viable". Provides data-driven analysis using web search, market frameworks, competitive research, and positioning recommendations.
ddgs
itsmeadarsh2008
Use when an agent needs to search the web, find images/news/videos/books, or extract content from a URL. Covers the ddgs Python library, CLI, and MCP server integration.
a-share-research-digest
aifinlab
A股研报摘要/卖方观点汇总/券商研报速览。当用户说"研报"、"券商研报"、"分析师怎么看"、"卖方观点"、"research digest"、"XX最新研报"、"目标价"、"评级"、"研究报告"、"机构怎么说"、"研报摘要"、"分析师观点"、"研报汇总"时触发。MUST USE when user asks about research report digest, analyst opinions/ratings/target prices, or sell-side consensus views on a stock. 通过 web 搜索汇总券商研报的核心观点、目标价、评级变化，帮助用户
deep-research
inuishan
Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution. Use when the user wants thorough research on any topic with evidence and citations.
exa-search
akghosh111
Semantic search skill using Exa API for embeddings-based search, similar content discovery, and structured research. Use when you need semantic search, find similar pages, or category-specific searches. Triggers: exa, semantic search, find similar, research paper, github search, 语义搜索, 相似内容