ホーム/データ&AI/tavily-research
T

tavily-research

by @tavily-aiv
4.5(104)

Tavily ResearchはAI駆動の深層研究を提供し、情報源を収集・分析してレポートを生成し、研究効率と品質を向上させます。

ai-researchdeep-researchinformation-gatheringdata-analysisGitHub
インストール方法
npx skills add tavily-ai/skills --skill tavily-research
compare_arrows

Before / After 効果比較

1
使用前

従来の調査では、資料の手動収集と分析が必要で、時間と労力がかかり、効率が低い。

使用後

AI駆動の深度研究は、情報源を自動的に収集・分析し、迅速に洞察を得る。

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

Weekly Installs465Repositorytavily-ai/skillsGitHub Stars95First Seen2 days agoSecurity AuditsGen Agent Trust HubPassSocketPassSnykFailInstalled oncodex457opencode456cursor456kimi-cli455gemini-cli455amp455

ユーザーレビュー (0)

レビューを書く

効果
使いやすさ
ドキュメント
互換性

レビューなし

統計データ

インストール数10.4K
評価4.5 / 5.0
バージョン
更新日2026年5月23日
比較事例1 件

ユーザー評価

4.5(104)
5
23%
4
52%
3
23%
2
2%
1
0%

この Skill を評価

0.0

対応プラットフォーム

🔧Claude Code

タイムライン

作成2026年3月18日
最終更新2026年5月23日