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npx skills add https://github.com/tavily-ai/skills --skill tavily-cli
Web search, content extraction, site crawling, URL discovery, and deep research. Returns JSON optimized for LLM consumption.
Run tvly --help or tvly <command> --help for full option details.
Must be installed and authenticated. Check with tvly --status.
tavily v0.1.0
> Authenticated via OAuth (tvly login)
If not ready:
curl -fsSL https://cli.tavily.com/install.sh | bash
Or manually: uv tool install tavily-cli / pip install tavily-cli
Then authenticate:
tvly login --api-key tvly-YOUR_KEY
# or: export TAVILY_API_KEY=tvly-YOUR_KEY
# or: tvly login (opens browser for OAuth)
Follow this escalation pattern — start simple, escalate when needed:
| Need | Command | When |
|------|---------|------|
| Find pages on a topic | tvly search | No specific URL yet |
| Get a page's content | tvly extract | Have a URL |
| Find URLs within a site | tvly map | Need to locate a specific subpage |
| Bulk extract a site section | tvly crawl | Need many pages (e.g., all /docs/) |
| Deep research with citations | tvly research | Need multi-source synthesis |
For detailed command reference, use the individual skill for each command (e.g., tavily-search, tavily-crawl) or run tvly <command> --help.
All commands support --json for structured, machine-readable output and -o to save to a file.
tvly search "react hooks" --json -o results.json
tvly extract "https://example.com/docs" -o docs.md
tvly crawl "https://docs.example.com" --output-dir ./docs/
? and & as special characters.--json for agentic workflows — every command supports it.- — echo "query" | tvly search -Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
React Native and Expo best practices for building performant mobile apps. Use when building React Native components, optimizing list performance, implementing animations, or working with native modules. Triggers on tasks involving React Native, Expo, mobile performance, or native platform APIs.
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
Next.js best practices - file conventions, RSC boundaries, data patterns, async APIs, metadata, error handling, route handlers, image/font optimization, bundling
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
Take tavily-ai/tavily-cli from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference pip.
Without those the skill loads but fails at the first command.