tavily-web-search

Purpose

This skill enables AI agents to perform web searches using Tavily, a service optimized for AI workflows. It synthesizes answers from search results, applies domain filters, and controls search depth to deliver relevant, concise information without overwhelming the agent.

When to Use

Use this skill when you need real-time web data, such as fetching current news, verifying facts, or gathering research. Apply it in scenarios where standard search engines are too verbose, like synthesizing answers for user queries, filtering results to specific domains (e.g., .edu sites), or limiting depth for quick responses. Avoid it for internal data access or when offline sources suffice.

Key Capabilities

• Answer Synthesis: Automatically summarizes search results into a coherent response; specify via search_depth parameter (e.g., 0 for shallow, 5 for deep).
• Domain Filtering: Restrict searches to domains like "example.com" using the include_domains flag; example: include_domains=["wikipedia.org"].
• Depth Control: Set search depth with max_results (1-10) to control result volume; higher values increase detail but raise costs.
• Optimized for AI: Integrates with AI agents via API, supporting tags like "search" and "ai" for metadata embedding.
• Configurable Queries: Supports query parameters for customization, such as query string and api_key for authentication.

Usage Patterns

Always initialize with an API key via environment variable $TAVILY_API_KEY. For basic searches, construct a query object and call the API endpoint. Use in loops for iterative refinement, e.g., refine queries based on initial results. Pattern: Set up auth, build query with filters, execute search, then parse and synthesize the response. For agent workflows, integrate as a subtool in multi-step processes, ensuring error checks between calls.