From tavily
Runs Tavily CLI for AI-powered web research, synthesizing sources into cited structured reports. For deep analysis, comparisons, market reviews, literature reviews (30-120s).
npx claudepluginhub tavily-ai/skills --plugin tavilyThis skill is limited to using the following tools:
AI-powered deep research that gathers sources, analyzes them, and produces a cited report. Takes 30-120 seconds.
Executes autonomous multi-step research with Google Gemini agent, producing cited reports for market analysis, competitive landscaping, technical reviews, and due diligence. Takes 2-10 min; costs $2-5.
Performs deep research on 11 types (market, technical, competitive, academic, etc.) via parallel web searches, multi-source validation, confidence scores, and cited Markdown reports.
Conducts AI-powered deep research on any topic via triggers like '/deep-research [topic]' or 'deep research on [topic]'. Uses interactive AskUserQuestion for focus, output, and audience selection.
Share bugs, ideas, or general feedback.
AI-powered deep research that gathers sources, analyzes them, and produces a cited report. Takes 30-120 seconds.
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.
# 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
| 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 | 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.
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
--stream to see progress in real-time.--model pro for complex comparisons or multi-faceted topics.--output-schema to get structured JSON output matching a custom schema.tvly search instead — research is for deep synthesis.echo "query" | tvly research - --json