Deepagents Typescript Quickstart
Scaffold a minimal local Deep Agent in TypeScript by following the official quickstart, using provider-native web search instead of Tavily. Use when the user wants to quickly build or try a Deep Agent locally.
- Skill ID
- langchain-ai/langchain-skills/deepagents-typescript-quickstart
- Publisher
- langchain-ai
- Repository
- langchain-skills
- Installs
- 0
- Files
- 1
- Synced
- Sep 23, 2026
Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.
langchain-ai/langchain-skills/deepagents-typescript-quickstartInstalls these files- SKILL.md
What this skill tells the agent
Deep Agents TypeScript quickstart
Follow the live docs — do not invent an alternate API from memory:
https://docs.langchain.com/oss/javascript/deepagents/quickstart
Fetch that page (Docs MCP or HTTP) and implement the research-agent shape it shows (createDeepAgent, research system prompt, invoke with a research question like “What is LangGraph?”). Requires Node 22+.
Local setup constraints
Apply these on top of the quickstart (they keep setup minimal and model-agnostic):
- Ask which provider/model to use. Showcase that Deep Agents are model-agnostic. Suggested prompt:
Which model should this agent use? Pass aprovider:modelstring — e.g.openai:gpt-5.5,anthropic:claude-sonnet-5,google-genai:gemini-3.5-flash. Default if you're unsure: `anthropic:claude-sonnet-5`. We'll use that provider's built-in web search (no separate search API key).
- Create a new directory (e.g.
deep-agent/) and do all work there — do not pollute the open project.
- Do not use Tavily (or
@langchain/tavily). Replace the quickstart's search tool with the chosen provider's built-in web search. Look up the current export/tool shape on that provider's LangChain docs (examples as of writing — re-check if needed):
| Provider | Built-in search tool |
|---|---|
| Anthropic | @langchain/anthropic tools.webSearch_*() (or equivalent dict) |
| OpenAI | { type: "web_search" } |
{ google_search: {} } |
Prefer Anthropic / OpenAI / Google so provider search is available. Only secret: that provider's API key in .env (gitignored). Skip LangSmith tracing unless they ask.
- Install packages from the quickstart minus Tavily; add the provider package for their model.
- Run the research example, show output, then stop. Point to
deep-agents-core/ customization / Managed Deep Agents for next steps.
More from langchain-ai
Use this skill in a project
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