
Tavily Research
- 7 installs
- 1 repo stars
- Updated July 28, 2026
- tavily-ai/tavily-cursor-plugin
This is a copy of tavily-research by tavily-ai - installs and ranking accrue to the original listing.
Helps with ai & agent building tasks during AI-assisted development.
About
tavily-research is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted coding.
- tavily-research
- AI & Agent Building
- AI-coding skill
Tavily Research by the numbers
- 7 all-time installs (skills.sh)
- +2 installs in the week ending Aug 5, 2026 (Skillselion tracking)
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 7 |
|---|---|
| repo stars | ★ 1 |
| Last updated | July 28, 2026 |
| Repository | tavily-ai/tavily-cursor-plugin ↗ |
What it does
Helps with ai & agent building tasks during AI-assisted development.
Files
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
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" --jsonOptions
| 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.jsonTips
- Research takes 30-120 seconds — use
--streamto 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 searchinstead — research is for deep synthesis. - Read from stdin:
echo "query" | tvly research - --json
See also
- tavily-search — quick web search for simple lookups
- tavily-crawl — bulk extract from a site for your own analysis