skills/tavily-research/SKILL.md
Deep multi-source research with automatic citations via Tavily's Research API. Use when you need comprehensive analysis, comparisons, market research, or structured reports grounded in live web data. Takes 30–120 seconds.
npx skillsauth add giggle-official/storyclaw-assistant tavily-researchInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Conduct comprehensive, citation-backed research on any topic. Tavily performs multiple iterative web searches, synthesizes sources, and returns a structured report — no manual source gathering required.
Set TAVILY_API_KEY in ~/.openclaw/.env.local:
TAVILY_API_KEY=tvly-your-api-key-here
Prefer tavily-search for quick single-topic lookups where you just need a list of results.
Note: Research takes 30–120 seconds. Set user expectations accordingly before starting.
The Research API is asynchronous: you submit a task, then poll for results.
Step 1 — Submit research task:
POST https://api.tavily.com/research
Step 2 — Poll for status/results:
GET https://api.tavily.com/research/{task_id}
curl -s -X POST https://api.tavily.com/research \
-H "Authorization: Bearer $TAVILY_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"input": "Compare LangGraph vs CrewAI for multi-agent systems in 2025",
"model": "pro"
}'
Response:
{
"task_id": "res_abc123xyz",
"status": "pending"
}
| Field | Type | Default | Description |
| ------- | ------ | ------------ | -------------------------- |
| input | string | Required | Research topic or question |
| model | string | "mini" | mini / pro / auto |
| Model | Best For | Typical Time |
| ------ | ------------------------------------------ | ------------ |
| mini | Single topic, targeted question | ~30s |
| pro | Multi-angle analysis, comparisons, reports | 60–120s |
| auto | Let Tavily decide based on complexity | Varies |
Rule of thumb: "What does X do?" → mini. "X vs Y vs Z" or "best way to..." → pro.
curl -s -X GET https://api.tavily.com/research/res_abc123xyz \
-H "Authorization: Bearer $TAVILY_API_KEY"
Response when complete:
{
"task_id": "res_abc123xyz",
"status": "completed",
"report": "## LangGraph vs CrewAI\n\n...",
"sources": [
{
"title": "LangGraph Documentation",
"url": "https://langchain-ai.github.io/langgraph/",
"content": "..."
}
]
}
Poll every 5–10 seconds until status is "completed" or "failed".
# Submit
curl -s -X POST https://api.tavily.com/research \
-H "Authorization: Bearer $TAVILY_API_KEY" \
-H "Content-Type: application/json" \
-d '{"input": "What is retrieval augmented generation?", "model": "mini"}'
# Poll with task_id from response
curl -s https://api.tavily.com/research/{task_id} \
-H "Authorization: Bearer $TAVILY_API_KEY"
curl -s -X POST https://api.tavily.com/research \
-H "Authorization: Bearer $TAVILY_API_KEY" \
-H "Content-Type: application/json" \
-d '{"input": "Fintech startup landscape 2025 key players funding trends", "model": "pro"}'
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