tavily-search

Search the web and return structured JSON results with relevance scores.

1|Updated May 10, 2026

Search Tags:#research #web-search #tavily #json-output #llm-optimized #domain-filtering

Ready to run

npx skills add https://github.com/a2ajinkya/phone-pi --skill tavily-search-a2ajinkya

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: tavily-search
Source: https://github.com/a2ajinkya/phone-pi/tree/main/skills/tavily-search
Command: npx skills add https://github.com/a2ajinkya/phone-pi --skill tavily-search-a2ajinkya

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Web research often requires collecting current information from multiple sources quickly; this skill provides fast, structured web search results with relevance scoring and metadata to feed AI workflows.

Core Features & Use Cases

Web search using the Tavily CLI with structured JSON output
Domain and time-range filters, multiple search depths
Use cases: quick background research, fact-checking, and source discovery across domains

Quick Start

Run a basic search with tvly search "your query" --json to retrieve structured results.

Frequently Asked Questions about tavily-search

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I get structured JSON output from a web search for my AI workflow?▼

Structured JSON output from a web search is generated by running a query with the Tavily CLI, returning content snippets, relevance scores, and metadata optimized for downstream AI workflows.

Can I filter web search results by specific domains and time ranges?▼

Yes, web search results can be filtered using optional domain filters and time-range controls to narrow down source discovery and gather current information across specific domains.

What is the best way to collect current information from multiple sources for fact-checking?▼

Collecting current information for fact-checking is best handled by performing a web search with multiple search depths, returning diverse articles with relevance scores and metadata.

Does Tavily CLI require any external dependencies to perform quick background research?▼

No external dependencies are required to perform quick background research, as the skill operates independently using the Tavily CLI to retrieve LLM-optimized search results.

How does relevance scoring work in LLM-optimized web search results?▼

Relevance scoring in LLM-optimized web search results evaluates and ranks retrieved content snippets, providing metadata that helps downstream processing prioritize diverse articles across domains.