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/tavily-research

@778122e official
by Tavily AItavily-ai/skills488 stars
42
Run it yourself

Conduct comprehensive AI-powered research with citations via the Tavily CLI. Use this skill when the user wants deep research, a detailed report, a comparison, market analysis, literature review, or says "research", "investigate", "analyze in depth", "compare X vs Y", "what does the market look like for", or needs multi-source synthesis with explicit citations. Returns a structured report grounded in web sources. Takes 30-120 seconds. For quick fact-finding, use tavily-search instead.

Use this Skill: https://skilld.dev/gh/tavily-ai/skills/tavily-research

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SKILL.md

≈127 tokens for metadata: the name and description. ≈878 when used: this file.

Description uses 6.3% of example budget

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  • A shorter description leaves more room for other Skills. This entry exceeds our 1% size suggestion.

In our Claude Code example, all Skill names and descriptions share 8,000 characters. This Skill uses ≈507 characters, or 6.3%.

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Example settings and source

The example uses a 200k-token context and default Claude Code settings. The count includes the name, description, separators, and when_to_use when present. Codex also counts local file paths.

Skit's source and limits: Codex 0.160.1, Claude Code 2.1.292.

tavily research

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

Before running

Research requires authentication. Run the requested command directly when tvly is already authenticated; do not add a status check to every invocation.

If tvly is missing, follow the tavily-cli setup. If an installed CLI reports an authentication error, use tvly login for authentication only, or tvly init --skip-skills when guided verification is also useful. Browser-based OAuth is preferred when an interactive user can complete it. --no-browser prints the sign-in link instead of opening it, but still waits for a localhost callback. In an unattended agent or CI environment, leave authentication to the user or use a securely provided TAVILY_API_KEY. Do not start a second login immediately after guided setup has completed.

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.json

# 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 the JSON response to a 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

Source: SKILL.md on GitHub

Skill behaviors

skilld matched fixed text patterns in SKILL.md and file names. Patterns miss obfuscated code.

skilld run checks every file with the same patterns. It asks for approval before it loads a Skill with a behavior marked Needs approval.

Third-party checks

1 warning1mo4 checks · Risk SAFE
  • Gen Agent Trust Hub1mo

    The skill provides a safe interface to the Tavily CLI for conducting deep research. It follows security best practices by recommending secure API key management and limiting command execution to the vendor's tool.

  • Socket1mo

    No alerts

  • Snyk1mo

    Risk: MEDIUM · 1 issue

  • ZeroLeaks6mo

    1 finding · Score: 82/100

Provenance

Signed by skilld at 778122e. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub last week.

Steadyupdated last month

Capability

What it can do
Runs commands
All 1 allowed tools
Bash(tvly *)

Topics

  • CLI
  • tavily
  • research
  • web-search
  • citations
  • analysis
  • market-research
  • comparative-analysis
  • synthesis

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README badge for tavily-ai/skills/tavily-research

What it does

Conducts multi-source AI research via Tavily CLI, synthesizing web results into a cited report in 30-120 seconds. Use for deep analysis, comparisons, market reports, or literature reviews where quick searches are insufficient; supports mini/pro model selection and multiple citation formats.

Generated from the current SKILL.md.

Frequently asked

How long does research take?
30-120 seconds depending on the model. Use `mini` for targeted research (~30s) or `pro` for comprehensive analysis (~60-120s). Use `--stream` to see progress in real-time.
When should I use this instead of tavily-search?
Use this skill for deep synthesis, comparisons, market analysis, and literature reviews that require multi-source analysis with citations. Use tavily-search for quick fact-finding.
What citation formats are supported?
The skill supports numbered, MLA, APA, and Chicago citation formats via the `--citation-format` option.
Can I get structured JSON output?
Yes. Use `--json` for standard JSON output, or `--output-schema` with a path to a custom JSON schema for structured results matching your requirements.
Does this work asynchronously?
Yes. Use `--no-wait` to get a request_id immediately, then use `tvly research status` or `tvly research poll` to check on or retrieve results later.

Generated from the current SKILL.md. These answers refresh after source changes.