tavily-research

Comprehensive AI-powered research with multi-source synthesis and citations. Produces structured reports grounded in web sources, taking 30-120 seconds depending on model selection (mini for targeted queries, pro for complex comparisons) Supports multiple output formats: markdown reports, JSON with custom schemas, and configurable citation styles (numbered, MLA, APA, Chicago) Includes async workflow for long-running research via --no-wait , status , and poll commands, plus real-time streaming with --stream Best for deep analysis, market reports, literature reviews, and multi-angle comparisons; use tavily-search instead for quick fact-finding

INSTALLATION
npx skills add https://github.com/tavily-ai/skills --skill tavily-research
Run in your project or agent environment. Adjust flags if your CLI version differs.

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:

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-crawl — bulk extract from a site for your own analysis
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