tavily-research
Conduct comprehensive AI-powered research with citations via the Tavily CLI. Use this skill when the user wants deep research, a detailed report, a comparison, market analysis, literature review, or says "research", "investigate", "analyze in depth", "compare X vs Y", "what does the market look like for", or needs multi-source synthesis with explicit citations. Returns a structured report grounded in web sources. Takes 30-120 seconds. For quick fact-finding, use tavily-search instead.
Best use case
tavily-research is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Conduct comprehensive AI-powered research with citations via the Tavily CLI. Use this skill when the user wants deep research, a detailed report, a comparison, market analysis, literature review, or says "research", "investigate", "analyze in depth", "compare X vs Y", "what does the market look like for", or needs multi-source synthesis with explicit citations. Returns a structured report grounded in web sources. Takes 30-120 seconds. For quick fact-finding, use tavily-search instead.
Teams using tavily-research should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/content-system-tavily-research/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How tavily-research Compares
| Feature / Agent | tavily-research | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Conduct comprehensive AI-powered research with citations via the Tavily CLI. Use this skill when the user wants deep research, a detailed report, a comparison, market analysis, literature review, or says "research", "investigate", "analyze in depth", "compare X vs Y", "what does the market look like for", or needs multi-source synthesis with explicit citations. Returns a structured report grounded in web sources. Takes 30-120 seconds. For quick fact-finding, use tavily-search instead.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# 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
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