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tavily-research

by @tavily-aiv1.0.0
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Tavily Research提供AI驱动的深度研究,收集、分析来源并生成报告,提高研究效率和质量。

AI ResearchDeep ResearchInformation GatheringData AnalysisGitHub
安装方式
npx skills add tavily-ai/skills --skill tavily-research
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Before / After 效果对比

1
使用前

传统研究需手动收集分析资料,耗时费力,效率低下。

使用后

AI驱动深度研究,自动收集分析来源,快速获取洞察。

description SKILL.md

tavily-research

tavily research AI-powered deep research that gathers sources, analyzes them, and produces a cited report. Takes 30-120 seconds. Before running any command If tvly is not found on PATH, install it first: curl -fsSL https://cli.tavily.com/install.sh | bash && tvly login Do not skip this step or fall back to other tools. See tavily-cli for alternative install methods and auth options. When to use You need comprehensive, multi-source analysis The user wants a comparison, market report, or literature review Quick searches aren't enough — you need synthesis with citations Step 5 in the workflow: search → extract → map → crawl → research Quick start # Basic research (waits for completion) tvly research "competitive landscape of AI code assistants" # Pro model for comprehensive analysis tvly research "electric vehicle market analysis" --model pro # Stream results in real-time tvly research "AI agent frameworks comparison" --stream # Save report to file tvly research "fintech trends 2025" --model pro -o fintech-report.md # JSON output for agents tvly research "quantum computing breakthroughs" --json Options Option Description --model mini, pro, or auto (default) --stream Stream results in real-time --no-wait Return request_id immediately (async) --output-schema Path to JSON schema for structured output --citation-format numbered, mla, apa, chicago --poll-interval Seconds between checks (default: 10) --timeout Max wait seconds (default: 600) -o, --output Save output to file --json Structured JSON output Model selection Model Use for Speed mini Single-topic, targeted research ~30s pro Comprehensive multi-angle analysis ~60-120s auto API chooses based on complexity Varies Rule of thumb: "What does X do?" → mini. "X vs Y vs Z" or "best way to..." → pro. Async workflow For long-running research, you can start and poll separately: # Start without waiting tvly research "topic" --no-wait --json # returns request_id # Check status tvly research status <request_id> --json # Wait for completion tvly research poll <request_id> --json -o result.json Tips Research takes 30-120 seconds — use --stream to see progress in real-time. Use --model pro for complex comparisons or multi-faceted topics. Use --output-schema to get structured JSON output matching a custom schema. For quick facts, use tvly search instead — research is for deep synthesis. Read from stdin: echo "query" | tvly research - --json See also tavily-search — quick web search for simple lookups tavily-crawl — bulk extract from a site for your own analysis Weekly Installs269Repositorytavily-ai/skillsGitHub Stars95First Seen2 days agoSecurity AuditsGen Agent Trust HubPassSocketPassSnykFailInstalled oncursor265github-copilot264gemini-cli264kimi-cli264codex264opencode264

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安装量0
评分0.0 / 5.0
版本1.0.0
更新日期2026年3月18日
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🔧Claude Code

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创建2026年3月18日
最后更新2026年3月18日