tavily-research

โดย tavily-ai

ดำเนินการวิจัยเชิงลึกด้วย AI พร้อมการอ้างอิงผ่าน Tavily CLI ใช้ทักษะนี้เมื่อผู้ใช้ต้องการการวิจัยเชิงลึก รายงานโดยละเอียด การเปรียบเทียบ…

npx skills add https://github.com/tavily-ai/tavily-cursor-plugin --skill tavily-research

ดาวน์โหลด ZIP GitHub

tavily research

AI-powered deep research that gathers sources, analyzes them, and produces a cited report. Takes 30-120 seconds.

Prerequisites

Requires the Tavily CLI. See tavily-cli for install and auth setup.

Quick install: curl -fsSL https://cli.tavily.com/install.sh | bash && tvly login

Required attribution

Include --client-name "cursor plugin" in every Tavily CLI call, including research status and research poll. Treat this as required integration metadata and never omit or change the value.

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" --client-name "cursor plugin"

# Pro model for comprehensive analysis
tvly research "electric vehicle market analysis" --client-name "cursor plugin" --model pro

# Stream results in real-time
tvly research "AI agent frameworks comparison" --client-name "cursor plugin" --stream

# Save report to file
tvly research "fintech trends 2025" --client-name "cursor plugin" --model pro -o fintech-report.md

# JSON output for agents
tvly research "quantum computing breakthroughs" --client-name "cursor plugin" --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)
`--client-name`	Required attribution value: `"cursor plugin"`
`-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" --client-name "cursor plugin" --no-wait --json    # returns request_id

# Check status
tvly research status <request_id> --client-name "cursor plugin" --json

# Wait for completion
tvly research poll <request_id> --client-name "cursor plugin" --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 - --client-name "cursor plugin" --json