Deepagents Python Quickstart
Scaffold a minimal local Deep Agent in Python 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.
Overview
Deepagents Python Quickstart is a SKILL.md workflow from langchain-ai/langchain-skills. It is categorized under research and links back to its reviewed source so users can inspect the complete instructions and bundled resources before installation.
Use Cases
Install Notes
# Review source first
open https://github.com/langchain-ai/langchain-skills/blob/main/config/skills/deepagents-python-quickstart/SKILL.mdCopy the reviewed skill folder into the skills directory used by your compatible agent.
Security Notes
AIToolly validated the published source structure and license automatically. Review langchain-ai/langchain-skills and any bundled scripts again before granting workspace, command, or network access.
Related Skills
Deepagents Typescript Quickstart
langchain-ai/langchain-skills
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.
Documentation Lookup
mxyhi/ok-skills
Retrieve current documentation and code examples for any library using the Context7 CLI.
Autoresearch — Autonomous Goal-directed Iteration
mxyhi/ok-skills
Autonomous iteration loop: modify, verify, keep/discard against any metric
Exa
mxyhi/ok-skills
Use Exa for web/code/company research (web_search_exa / get_code_context_exa / company_research_exa), with parameters and examples; trigger when online search or parameter checks are needed.
Get API Docs via chub
mxyhi/ok-skills
When you need documentation for a library or API, fetch it with the chub CLI rather than guessing from training data. This gives you the current, correct API.
A2A Protocol
TerminalSkills/skills
Implements the Agent2Agent (A2A) open protocol for communication between AI agents built on different frameworks. A2A enables agents to discover each other via Agent Cards, negotiate interaction modalities, manage collaborative tasks, and exchange data — all without exposing internal state, memory, or tools. Supports J