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Agent Skills let you add Tavily’s web capabilities to AI coding agents like Claude Code, Cursor, Cline, Codex, Windsurf, and others via the Tavily CLI.

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Available Skills

SkillDescription
tavily-searchWeb search with agent-optimized results.
tavily-extractExtract clean markdown/text from URLs.
tavily-crawlCrawl a website and extract content from multiple pages with semantic filtering.
tavily-mapDiscover and list all URLs on a website.
tavily-researchAI-powered research that produces a cited report.
tavily-best-practicesReference docs for building production-ready Tavily integrations.

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Installation

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Step 1:

Install the Tavily CLI: 
curl -fsSL https://cli.tavily.com/install.sh | bash
See the CLI docs for other installation methods.

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Step 2:

Install the skills: 
npx skills add tavily-ai/skills --all
Or install a specific skill: 
npx skills add tavily-ai/skills --skill tavily-search
After installation, restart your AI agent to load the skills.

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Usage

Once installed, skills are automatically available to your agent. No additional configuration is needed — your agent will use them when appropriate based on your prompts.

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Automatic Invocation

Simply describe what you need and your agent will use the right Tavily skill: 
Search for the latest news on AI regulations

Crawl the Stripe API docs and save them locally

Research the competitive landscape for AI coding assistants

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Explicit Skill Invocation

You can also invoke skills directly using slash commands: 
/tavily-search current React best practices

/tavily-extract https://example.com/blog/post

/tavily-crawl https://docs.example.com

/tavily-research AI agent frameworks and save to report.json

/tavily-best-practices

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Skill Details

Search

Extract clean markdown or text content from one or more URLs. Handles JavaScript-rendered pages.Invoke explicitly:
/tavily-extract
Example prompts:
  • “Extract the content from this article URL”
  • “/tavily-extract https://example.com/blog/post”
  • “Extract content from these three documentation pages”
CLI usage:
# Single URL
tvly extract "https://example.com/article" --json

# Multiple URLs
tvly extract "https://example.com/page1" "https://example.com/page2" --json

# Query-focused extraction (returns relevant chunks only)
tvly extract "https://example.com/docs" --query "authentication API" --chunks-per-source 3 --json
Key options: --query, --chunks-per-source, --extract-depth (basic/advanced), --format (markdown/text)
Discover URLs on a website without extracting content. Faster than crawling — useful for finding the right page before extracting.Invoke explicitly:
/tavily-map
Example prompts:
  • “Map the site structure of docs.example.com”
  • “Find the authentication page on this site”
  • “List all URLs under the /api/ path”
CLI usage:
# Discover all URLs
tvly map "https://docs.example.com" --json

# With natural language filtering
tvly map "https://docs.example.com" --instructions "Find API docs and guides" --json

# Filter by path
tvly map "https://example.com" --select-paths "/blog/.*" --limit 500 --json
Key options: --max-depth, --limit, --instructions, --select-paths, --exclude-paths
Use the map + extract pattern: map to find the right page, then extract its content. This is often more efficient than crawling an entire site.
Crawl websites and extract content from multiple pages. Save each page as a local markdown file or get structured JSON output.Invoke explicitly:
/tavily-crawl
Example prompts:
  • “Crawl the Stripe API docs and save them locally”
  • “/tavily-crawl https://docs.example.com”
  • “Download the Next.js documentation for offline reference”
CLI usage:
# Save each page as a markdown file
tvly crawl "https://docs.example.com" --output-dir ./docs/

# Semantic focus (returns relevant chunks, not full pages)
tvly crawl "https://docs.example.com" --instructions "Find authentication docs" --chunks-per-source 3 --json

# Filter to specific paths
tvly crawl "https://example.com" --select-paths "/api/.*,/guides/.*" --exclude-paths "/blog/.*" --json
Key options: --max-depth, --limit, --instructions, --chunks-per-source, --output-dir, --select-paths, --exclude-paths
AI-powered deep research that gathers sources, analyzes them, and produces a cited report. Takes 30–120 seconds.Invoke explicitly:
/tavily-research
Example prompts:
  • “Research the latest developments in quantum computing”
  • “/tavily-research AI agent frameworks and save to report.json”
  • “Research the competitive landscape for AI coding assistants”
CLI usage:
# Basic research
tvly research "competitive landscape of AI code assistants"

# Pro model for comprehensive analysis
tvly research "electric vehicle market analysis" --model pro

# Stream results in real-time
tvly research "AI agent frameworks comparison" --stream

# Save report to file
tvly research "fintech trends 2025" --model pro -o report.md
Key options: --model (mini/pro/auto), --stream, --citation-format, --output-schema, -o
Build production-ready Tavily integrations with best practices baked in. Reference documentation for implementing web search, content extraction, crawling, and research in agentic workflows, RAG systems, or autonomous agents.Invoke explicitly:
/tavily-best-practices
Example prompts:
  • “Add Tavily search to my internal company chatbot so it can answer questions about our competitors”
  • “Build a lead enrichment tool that uses Tavily to find company information from their website”
  • “Create a news monitoring agent that tracks mentions of our brand using Tavily search”
  • “Implement a RAG pipeline that uses Tavily extract to pull content from industry reports”

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What You Can Build

Copy-paste these prompts into your AI agent and start building:
Create a live news dashboard that tracks topics and analyzes sentiment.Try these prompts:
/tavily-best-practices Build a website that refreshes daily with Tesla news and gives a sentiment score on each article

/tavily-best-practices Create a news monitoring dashboard that tracks AI industry news and sends daily Slack summaries
Build tools that automatically enrich leads with company data from the web.Try these prompts:
/tavily-best-practices Build a lead enrichment tool that uses Tavily to find company information from their website

/tavily-best-practices Create a script that takes a list of company URLs and extracts key business information
Build an autonomous agent that monitors competitors and surfaces insights.Try these prompts:
/tavily-best-practices Build a market research tool that crawls competitor documentation and pricing pages

/tavily-best-practices Create an agent that monitors competitor product launches and generates weekly reports
The /tavily-best-practices skill is your fastest path to production. Describe what you want to build and your agent generates working code with best practices baked in.