---
id: sm3-tavily-research
name: "tavily-research"
url: https://skills.yangsir.net/skill/sm3-tavily-research
author: tavily-ai
domain: data-ai
tags: ["ai-research", "deep-research", "information-gathering", "data-analysis"]
install_count: 10400
rating: 4.50 (104 reviews)
github: https://github.com/tavily-ai/skills
---

# tavily-research

> 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。

**Stats**: 10,400 installs · 4.5/5 (104 reviews)

## Before / After 对比

### Tavily AI深度研究

## Readme

# 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](https://github.com/tavily-ai/skills/blob/HEAD/skills/tavily-research/../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](https://github.com/tavily-ai/skills/blob/HEAD/skills/tavily-research/../tavily-cli/SKILL.md): 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](https://github.com/tavily-ai/skills/blob/HEAD/skills/tavily-research/../tavily-search/SKILL.md) — quick web search for simple lookups

- [tavily-crawl](https://github.com/tavily-ai/skills/blob/HEAD/skills/tavily-research/../tavily-crawl/SKILL.md) — bulk extract from a site for your own analysis

Weekly Installs465Repository[tavily-ai/skills](https://github.com/tavily-ai/skills)GitHub Stars95First Seen2 days agoSecurity Audits[Gen Agent Trust HubPass](/tavily-ai/skills/tavily-research/security/agent-trust-hub)[SocketPass](/tavily-ai/skills/tavily-research/security/socket)[SnykFail](/tavily-ai/skills/tavily-research/security/snyk)Installed oncodex457opencode456cursor456kimi-cli455gemini-cli455amp455

---
*Source: https://skills.yangsir.net/skill/sm3-tavily-research*
*Markdown mirror: https://skills.yangsir.net/api/skill/sm3-tavily-research/markdown*