tavily-research
Thực hiện nghiên cứu toàn diện với sức mạnh AI kèm trích dẫn thông qua Tavily CLI. Sử dụng kỹ năng này khi người dùng muốn nghiên cứu chuyên sâu, báo cáo chi tiết, so sánh,…
npx skills add https://github.com/tavily-ai/tavily-cursor-plugin --skill tavily-researchtavily 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
--streamto see progress in real-time. - Use
--model profor complex comparisons or multi-faceted topics. - Use
--output-schemato get structured JSON output matching a custom schema. - For quick facts, use
tvly searchinstead — research is for deep synthesis. - Read from stdin:
echo "query" | tvly research - --client-name "cursor plugin" --json
See also
- tavily-search — quick web search for simple lookups
- tavily-crawl — bulk extract from a site for your own analysis