Tavily Web Search
allenpeng0705/EnvoyMesh
Searches the web through the Tavily API with LLM-friendly output: clean structured results, optional AI-written answers, domain filters, news mode, images and raw content.
Advanced web search, content extraction, and site mapping through Tavily via SandBase.
Install Tavily Deep Research
$ npx skills add sandbaseai/sandbase-skills --skill tavily-deep-research -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install sandbaseai/sandbase-skills tavily-deep-research --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/sandbaseai/sandbase-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/research/tavily-deep-research .claude/skills/tavily-deep-research && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "tavily-deep-research" agent skill from https://github.com/sandbaseai/sandbase-skills/tree/main/research/tavily-deep-research into .claude/skills/tavily-deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tavily-deep-research", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/sandbaseai/sandbase-skills/tree/main/research/tavily-deep-researchType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add sandbaseai/sandbase-skills --skill tavily-deep-research -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install sandbaseai/sandbase-skills tavily-deep-research --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sandbaseai/sandbase-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/research/tavily-deep-research .agents/skills/tavily-deep-research && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "tavily-deep-research" agent skill from https://github.com/sandbaseai/sandbase-skills/tree/main/research/tavily-deep-research into .agents/skills/tavily-deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tavily-deep-research", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add sandbaseai/sandbase-skills --skill tavily-deep-research -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install sandbaseai/sandbase-skills tavily-deep-research --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sandbaseai/sandbase-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/research/tavily-deep-research .cursor/skills/tavily-deep-research && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "tavily-deep-research" agent skill from https://github.com/sandbaseai/sandbase-skills/tree/main/research/tavily-deep-research into .cursor/skills/tavily-deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tavily-deep-research", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/sandbaseai/sandbase-skills.git --path research/tavily-deep-research--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add sandbaseai/sandbase-skills --skill tavily-deep-research -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install sandbaseai/sandbase-skills tavily-deep-research --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sandbaseai/sandbase-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/research/tavily-deep-research .gemini/skills/tavily-deep-research && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "tavily-deep-research" agent skill from https://github.com/sandbaseai/sandbase-skills/tree/main/research/tavily-deep-research into .gemini/skills/tavily-deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tavily-deep-research", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install sandbaseai/sandbase-skills tavily-deep-researchInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add sandbaseai/sandbase-skills --skill tavily-deep-research -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/sandbaseai/sandbase-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/research/tavily-deep-research .github/skills/tavily-deep-research && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "tavily-deep-research" agent skill from https://github.com/sandbaseai/sandbase-skills/tree/main/research/tavily-deep-research into .github/skills/tavily-deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tavily-deep-research", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add sandbaseai/sandbase-skills --skill tavily-deep-research -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install sandbaseai/sandbase-skills tavily-deep-research --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sandbaseai/sandbase-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/research/tavily-deep-research .opencode/skills/tavily-deep-research && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "tavily-deep-research" agent skill from https://github.com/sandbaseai/sandbase-skills/tree/main/research/tavily-deep-research into .opencode/skills/tavily-deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tavily-deep-research", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
tavily-deep-research- GitHub stars
- 203
- Token cost
- ~699 tokens
- SKILL.md length
- 335 words
- Files
- 2 (incl. references)
- Skills in repo
- 23
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Advanced web search, content extraction, and site mapping through Tavily via SandBase.
- Works in 3 steps: Search the web → Extract content → Map site structure
- Asked for web research
- SKILL.md covers Call SandBase capabilities, Operating principles, Workflow and Output, plus 1 more section
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Tavily Deep Research is an agent skill from sandbaseai/sandbase-skills. Advanced web search, content extraction, and site mapping through Tavily via SandBase. Use when asked for web research, URL content extraction, full article reading, news search, or site structure discovery.
Its SKILL.md is about 700 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/sandbase-api-map.md`).
It sits in Productivity & Automation, covering Web search and Deep research. It works with Tavily. The repository describes itself as: 88 installable open-source Agent Skills for research, social intelligence, marketing, and business workflows—compatible with Codex, Claude Code, Cursor, Gemini CLI, and DeepSeek… The licence is Apache-2.0.
When your agent uses it
- Asked for web research
- URL content extraction
- Full article reading
- Site structure discovery
Example prompts
- “/tavily-deep-research”
Workflow steps
3 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit cbab581. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Tavily Deep Research loads about 699 tokens when it runs, and up to ~946 if it reads all its reference files. Until then it costs about 57 tokens; SKILL.md has 335 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from sandbaseai/sandbase-skills at commit cbab581, republished under its Apache-2.0 licence (© sandbaseai). 335 words, ~699 tokens.
Download SKILL.mdSave it as
.claude/skills/tavily-deep-research/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- tavily-deep-research
- description
- Advanced web search, content extraction, and site mapping through Tavily via SandBase. Use when asked for web research, URL content extraction, full article reading, news search, or site structure discovery.
Tavily Deep Research
Advanced web search and content extraction through SandBase's Tavily integration. Search the web with depth control, extract clean content from URLs, and discover site structures. Read the API map before selecting a capability.
Call SandBase capabilities
Use the capability identifiers below as discovery hints, not MCP tool names. Find the matching endpoint with sandbase_discover(q: "<provider and capability>"); use its returned name in sandbase_inspect(name: "<returned name>"). Read inputSchema, pricing, and execute_as, then call sandbase_run using execute_as.arguments.name and schema-defined arguments. If a run_id is returned, poll sandbase_run_get(run_id: "<returned run_id>") within the task budget until completed or failed; report pending or failed runs without resubmitting them automatically.
Operating principles
- Use Tavily for current, real-time web information that the model's training data may not cover.
- Cite sources with URLs for every factual claim.
- Use appropriate search depth: basic for quick checks, advanced for thorough research.
- Extract full content only when necessary — search snippets are often sufficient.
Workflow
1. Search the web
Use tavily_search with parameters:
search_depth: "basic" for quick validation, "advanced" for thorough researchtopic: "general", "news", or "finance" to focus resultsdays: limit to recent results (e.g., 7 for past week)max_results: 5-20 depending on coverage needsinclude_domains/exclude_domains: filter by source
2. Extract content
Use tavily_extract to get clean, readable content from specific URLs.
- Use when search snippets aren't enough and full article text is needed.
- Works on most public web pages — not paywalled content.
3. Map site structure
Use tavily_map to discover all pages on a website.
- Use for competitor site analysis or content auditing.
- Returns site structure and page list.
Output
Return: search results with source URLs, extracted content summaries, site maps when relevant, and confidence indicators.
Example tasks
- "Search the web for the latest news about [topic] in the last 7 days."
- "Extract the full content from this article: [URL]."
- "Research [topic] — find 10 authoritative sources and summarize key findings."
- "Map all pages on [website URL] to understand their content structure."
- "Find recent news about [company] and summarize the key developments."
© sandbaseai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 1 other file (references) in research/tavily-deep-research of sandbaseai/sandbase-skills.
- SKILL.md
- references/sandbase-api-map.md
Open the folder on GitHubat commit cbab581
Compare with similar skills
Tavily Deep Research next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Tavily Deep Research this skillsandbaseai/sandbase-skills | 203 | — | ~699 | Automated safety check: Pass | Apache-2.0 | |
| Tavily Web Searchallenpeng0705/EnvoyMesh | 3.1k | 3 repos | ~2.5k | Automated safety check: Notes | None | |
| Argo Search and Verificationtaxueseek/argo | 188 | — | ~1.2k | Automated safety check: Pass | MIT | |
| Tavily Web SearchLichAmnesia/lich-skills | 234 | — | ~1k | Automated safety check: Notes | MIT | |
| Omk ResearchKaimingWan/oh-my-kiro | 107 | — | ~827 | Automated safety check: Pass | MIT | |
| Tavily Researchinitializ/forge | 222 | — | ~1.1k | Automated safety check: Pass | Apache-2.0 |
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Related
Works with
Questions about Tavily Deep Research
What does Tavily Deep Research do?
Advanced web search, content extraction, and site mapping through Tavily via SandBase. Tavily Deep Research is an agent skill from sandbaseai/sandbase-skills. Advanced web search, content extraction, and site mapping through Tavily via SandBase.
When should I use Tavily Deep Research?
Tavily Deep Research fits situations like: asked for web research; URL content extraction; full article reading; site structure discovery.
How do I install Tavily Deep Research in Claude Code?
Run `npx skills add sandbaseai/sandbase-skills --skill tavily-deep-research -a claude-code`. Or copy the skill folder (research/tavily-deep-research in sandbaseai/sandbase-skills) into .claude/skills/tavily-deep-research in your project. Claude Code loads it when a task matches its description.
How do I install Tavily Deep Research in Codex?
Run `npx skills add sandbaseai/sandbase-skills --skill tavily-deep-research -a codex`. Or copy the skill folder (research/tavily-deep-research in sandbaseai/sandbase-skills) into .agents/skills/tavily-deep-research in your project. Codex loads it when a task matches its description.
Can I use Tavily Deep Research in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sandbaseai/sandbase-skills --skill tavily-deep-research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tavily-deep-research, .gemini/skills/tavily-deep-research, .github/skills/tavily-deep-research and .opencode/skills/tavily-deep-research in your project.
What does Tavily Deep Research need to run?
SKILL.md names no scripts, command-line tools or credentials: Tavily Deep Research is instructions for the agent only.
Does Tavily Deep Research access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Tavily Deep Research safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Tavily Deep Research use?
Tavily Deep Research is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Tavily Deep Research use?
About 699 tokens (SKILL.md is roughly 2.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 247 tokens, read only when the agent opens those files.
What are the alternatives to Tavily Deep Research?
Skills that share tags, products or a category with Tavily Deep Research: Tavily Web Search (allenpeng0705/EnvoyMesh, 3.1k stars), Argo Search and Verification (taxueseek/argo, 188 stars), Tavily Web Search (LichAmnesia/lich-skills, 234 stars) and Omk Research (KaimingWan/oh-my-kiro, 107 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Tavily Deep Research?
sandbaseai (a GitHub organization) maintains it in sandbaseai/sandbase-skills, which has 203 GitHub stars. The repository holds 23 skills in this directory. The repository was last updated on September 26, 2026.
Source: sandbaseai/sandbase-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.