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Tavily

OrganizationPopular
openclaw
tavily

Tavily web search, content extraction, and research tools.

Overview

Publisheropenclaw
Repositoryopenclaw
Skill nametavily
Stars
391K
Forks
82.2K
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by openclaw on GitHub. Read the source before you install it.

Installation

Install the Tavily AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/openclaw/openclaw/tree/main/extensions/tavily/skills/tavily
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/openclaw/openclaw.git /tmp/openclaw
mkdir -p .claude/skills
cp -r /tmp/openclaw/extensions/tavily/skills/tavily .claude/skills/tavily
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Tavily in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Tavily on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Tavily is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Tavily Tools

When to use which tool

NeedToolWhen
Quick web searchweb_searchBasic queries, no special options needed
Search with advanced optionstavily_searchNeed depth, topic, domain filters, time ranges, or AI answers
Extract content from URLstavily_extractHave specific URLs, need their content

web_search

Tavily powers this automatically when selected as the search provider. Use for straightforward queries where you don't need Tavily-specific options.

ParameterDescription
querySearch query string
countNumber of results (1-20)

tavily_search

Use when you need fine-grained control over search behavior.

ParameterDescription
querySearch query string (keep under 400 characters)
search_depthbasic (default, balanced) or advanced (highest relevance, slower)
topicgeneral (default), news (real-time updates), or finance
max_resultsNumber of results, 1-20 (default: 5)
include_answerInclude an AI-generated answer summary (default: false)
time_rangeFilter by recency: day, week, month, or year
include_domainsArray of domains to restrict results to
exclude_domainsArray of domains to exclude from results

Search depth

DepthSpeedRelevanceBest for
basicFasterHighGeneral-purpose queries (default)
advancedSlowerHighestPrecision, specific facts, detailed research

Tips

  • Keep queries under 400 characters — think search query, not prompt.
  • Break complex queries into sub-queries for better results.
  • Use include_domains to focus on trusted sources.
  • Use time_range for recent information (news, current events).
  • Use include_answer when you need a quick synthesized answer.

tavily_extract

Use when you have specific URLs and need their content. Handles JavaScript-rendered pages and returns clean markdown. Supports query-focused chunking for targeted extraction.

ParameterDescription
urlsArray of URLs to extract (1-20 per request)
queryRerank extracted chunks by relevance to this query
extract_depthbasic (default, fast) or advanced (for JS-heavy pages, tables)
chunks_per_sourceChunks per URL, 1-5 (requires query)
include_imagesInclude image URLs in results (default: false)

Extract depth

DepthWhen to use
basicSimple pages — try this first
advancedJS-rendered SPAs, dynamic content, tables, embedded content

Tips

  • Max 20 URLs per request — batch larger lists into multiple calls.
  • Use query + chunks_per_source to get only relevant content instead of full pages.
  • Try basic first, fall back to advanced if content is missing or incomplete.
  • If tavily_search results already contain the snippets you need, skip the extract step.

Choosing the right workflow

Follow this escalation pattern — start simple, escalate only when needed:

  1. web_search — Quick lookup, no special options needed.
  2. tavily_search — Need depth control, topic filtering, domain filters, time ranges, or AI answers.
  3. tavily_extract — Have specific URLs, need their full content or targeted chunks.

Combine search + extract when you need to find pages first, then get their full content.

Frequently asked questions

What does the Tavily AI skill do?

Tavily web search, content extraction, and research tools.

Why use Tavily on TypingMind?

Because you install it once and use it with any model. Tavily is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Tavily in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/openclaw/openclaw/tree/main/extensions/tavily/skills/tavily. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Tavily?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Tavily?

As many as you like. As long as a model supports skills, you can use Tavily with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Tavily AI skill free?

It is published on GitHub by openclaw. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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