tavily-best-practices
Build production-ready Tavily integrations with best practices baked in. Reference documentation for developers using coding assistants (Claude Code, Cursor, etc.) to implement web search, content extraction, crawling, and research in agentic workflows, RAG systems, or autonomous agents.
Install
With your agent
Install OMGSkills skill "tavily-ai/skills:tavily-best-practices" into this agent's normal skills directory: call the OMGSkills MCP get_install_plan tool for your agent and run the script it returns (it installs only the pinned commit and verifies SKILL.md), and stop if MCP or the pin is unavailable. Do not overwrite or change existing skills without asking me.
Manual command
git clone https://github.com/tavily-ai/skills /tmp/skills && ln -s /tmp/skills/skills/tavily-best-practices ~/.claude/skills/tavily-best-practicesFrom README
Tavily Tavily is a search API designed for LLMs, enabling AI applications to access real-time web data. Python: JavaScript: See references/sdk.md for complete SDK reference. Client Initialization Choosing the Right Method For custom agents/workflows: | Need | Method | |------|--------| | Web search results | search() | | Content from specific URLs | extract() | | Content from entire site | crawl() | | URL discovery from site | map() | For out-of-the-box research: | Need | Method | |------|--------| | End-to-end research with AI synthesis | research() | Quick Reference search() - Web Search Key parameters: query, maxresults, searchdepth (ultra-fast/fast/basic/advanced), includedomains, excludedomains, timerange See references/search.md for complete search reference. extract() - URL Content Extraction Key parameters: urls (max 20), extractdepth, query, chunkspersource (1-5) See references/extract.md for complete extract reference.