What is the Claude Agent SDK?

The Claude Agent SDK is Anthropic's official framework designed to help developers build production-ready AI agents that can use tools, manage their own conversation loops, and handle complex tasks autonomously.

Does this skill support both Python and TypeScript?

Yes, the skill provides patterns and guidance for both the Python (claude-agents) and TypeScript (@anthropics/agent-sdk) implementations of the SDK.

What is the benefit of using subagents?

Subagents allow for context isolation, meaning a main agent can delegate a specific, complex task to a specialized assistant without cluttering the primary conversation history with unnecessary details.

How do hooks work in the Agent SDK?

Hooks allow you to intercept the agent's lifecycle, enabling you to log tool usage, modify tool results, or block dangerous commands (like specific bash inputs) before they are executed.

Claude Agent SDK

Name: Claude Agent SDK
Author: rysweet

byrysweet

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Data Science & ML

Builds production-ready AI agents using Anthropic's official framework for tool orchestration and autonomous workflows.

About

The Claude Agent SDK skill provides specialized knowledge and implementation patterns for Anthropic’s official framework for building AI agents. It simplifies the creation of autonomous systems by handling the agent loop, tool execution, and context management automatically. This skill helps developers implement sophisticated features like subagent hierarchies for task decomposition, Model Context Protocol (MCP) integration for standardized tools, and lifecycle hooks for advanced observability and security. It is essential for anyone moving beyond simple chat completions into production-grade agentic workflows.

Key Features

Native Model Context Protocol (MCP) server integration
Automated agent loop management and tool orchestration
Extensive lifecycle hooks for tool validation and security
17 GitHub stars
Multi-agent delegation patterns with isolated subagent contexts
Intelligent context compaction and token budget optimization

Use Cases

Creating specialized research assistants using subagent hierarchies
Building autonomous coding agents with file system and terminal access
Implementing secure enterprise agents with tool-use permission layers

About

Key Features

Native Model Context Protocol (MCP) server integration
Automated agent loop management and tool orchestration
Extensive lifecycle hooks for tool validation and security
17 GitHub stars
Multi-agent delegation patterns with isolated subagent contexts
Intelligent context compaction and token budget optimization

Use Cases

Creating specialized research assistants using subagent hierarchies
Building autonomous coding agents with file system and terminal access
Implementing secure enterprise agents with tool-use permission layers