npx agentspec-cli install 74d006a4-8b95-470d-8949-73c4b92e1ecd --framework ClaudeCode→ .claude/skills/tavily-research/SKILL.md
# 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: ```bash 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](../tavily-cli/SKILL.md) 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](../tavily-cli/SKILL.md): search → extract → map → crawl → **research** ## Quick start ```bash # 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: ```bash # 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](../tavily-search/SKILL.md) — quick web search for simple lookups - [tavily-crawl](../tavily-crawl/SKILL.md) — bulk extract from a site for your own analysis
Built on the Agent Skills standard
tavily-cli
Web search, content extraction, crawling, and deep research via the Tavily CLI. Use this skill whenever the user wants to search the web, find articles, research a topic, look something up online, extract content from a URL, grab text from a webpage, crawl documentation, download a site's pages, discover URLs on a domain, or conduct in-depth research with citations. Also use when they say "fetch this page", "pull the content from", "get the page at https://", "find me articles about", or reference extractin
by AgentHub Crawler
tavily-search
Search the web with LLM-optimized results via the Tavily CLI. Use this skill when the user wants to search the web, find articles, look up information, get recent news, discover sources, or says "search for", "find me", "look up", "what's the latest on", "find articles about", or needs current information from the internet. Returns relevant results with content snippets, relevance scores, and metadata — optimized for LLM consumption. Supports domain filtering, time ranges, and multiple search depths.
by AgentHub Crawler
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tavily-best-practices
Build production-ready Tavily integrations with best practices baked in. Reference documentation for developers using coding assistants (Claude Code, Cursor, etc.) to implement web search, content extraction, crawling, and research in agentic workflows, RAG systems, or autonomous agents.
by AgentHub Crawler