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Web search optimized for AI agents with real-time data retrieval. \n \n Single command interface ( scripts/search ) for querying the web with results tailored for agent consumption \n Supports JSON output formatting for structured data integration into agent workflows \n Requires Tavily API key for authentication; free API key available from tavily.com \n

Web search and content extraction via Tavily and Exa APIs through inference.sh CLI. \n \n Five search and extraction apps: Tavily Search Assistant (AI-powered answers with sources), Tavily Extract (multi-URL content extraction), Exa Search (smart web search), Exa Answer (direct factual responses), and Exa Extract (web page analysis) \n Designed for research workflows, RAG pipelines, fact-checking, and content aggregation with LLM integration examples \n Requires inference.sh CLI ( infsh ) instal

Modern file and content search.

The useSearchParams hook requires TWO things:

This skill automates the process of extracting high-quality multi-modal content (text + images) from Xiaohongshu (小红书) and actively assists you in generating a deeply integrated, analytical final report for the user. Due to Xiaohongshu's aggressive anti-scraping mechanisms, direct HTTP requests or naive scraping often result in 404s or blocks. This skill natively bypasses these by simulating a real user through the playwright-cli in a headed browser window.

Category: test

SwiftUI search is environment-based and navigation-consumed. You attach .searchable() to a view, but a navigation container (NavigationStack, NavigationSplitView, or TabView) renders the actual search field. This indirection is the source of most search bugs.

$1f

$22

Scope: Optimizing content for AI-powered search engines and answer engines This skill covers strategies for visibility in ChatGPT, Perplexity, Google AI Overviews, Microsoft Copilot, and other generative AI platforms.