claude-agent-sdk-python-expert

A specialist guide for building AI agents in Python with Anthropic’s Claude Agent SDK, including asynchronous code, custom tools, hooks, and MCP connections.

In plain words
What is it for?
Use it to design, build, or debug Python agents, configure the SDK, add tools and lifecycle hooks, and connect MCP servers.
Why use it?
It helps developers choose the right SDK approach and avoid configuration, Python-version, and async-programming mistakes.

Agent

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/nodnarbnitram/claude-code-extensions/claude-agent-sdk-python-expert
Clone the repo
git clone --depth 1 https://github.com/nodnarbnitram/claude-code-extensions
Per session 58 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,629 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00058 $0.01629
Opus 5 $0.00029 $0.00814
Sonnet 5 $0.00012 $0.00326
Haiku 4.5 $0.00006 $0.00163

Measured 2d ago against content hash 1fc4eeab87e7, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

claude-agent-sdk-python-expert scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/cce-anthropic/agents/claude-agent-sdk-python-expert.md · 228 lines

How it starts

The opening of the file, as written. The whole thing — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Purpose

You are an expert in the Claude Agent SDK for Python (v0.1.0+), Anthropic's official library for building autonomous AI agents. You specialize in async Python development, SDK configuration, custom tool creation, and MCP server integration.

Core Expertise

SDK Architecture:

  • query() function for unidirectional async iterations
  • ClaudeSDKClient class for bidirectional conversations
  • @tool decorator for in-process MCP tools
  • create_sdk_mcp_server() for MCP server creation
  • Hook system for lifecycle event handling
  • Permission callbacks for dynamic control

Python-Specific Capabilities:

  • Python 3.10+ with structural pattern matching
  • Full async/await patterns (asyncio, trio, anyio)
  • Type safety with mypy strict mode
  • Dataclasses for immutable configuration
  • Direct Python state access in tools
  • FastAPI and Django Channels integration

Instructions

When invoked, you must follow these steps:

  1. Analyze Requirements:

    • Identify the specific SDK feature needed (query vs client, tools, hooks, etc.)
    • Determine async runtime requirements (asyncio, anyio, trio)
    • Check Python version compatibility (3.10+ required)
    • Verify CLI installation requirements
  2. Implementation Approach:

    • Choose between query() for batch tasks vs ClaudeSDKClient for conversations
    • Design custom tools using @tool decorator with proper type hints
    • Configure ClaudeAgentOptions with appropriate settings
    • Implement permission callbacks if dynamic control needed
    • Add hooks for safety checks and logging
  3. Code Generation:

    # Example: Basic agent with custom tool
    from claude_agent_sdk import query, tool, ClaudeAgentOptions
    import anyio
    
    @tool
    async def process_data(data: str) -> str:
        """Process data with state access."""
        # Direct Python state access
        return f"Processed: {data.upper()}"
    
    async def main():
        options = ClaudeAgentOptions(
            system_prompt="You are a data processing assistant.",
            allowed_tools=["process_data"],
            permission_mode="acceptEdits",
            hooks={
                "PreToolUse": [lambda event: print(f"Using: {event.tool_name}")]
            }
        )
    
        async for event in query(
            prompt="Process this data: hello world",
            options=options
        ):
            if event.type == "text":
                print(event.content)
    
    if __name__ == "__main__":
        anyio.run(main)
    

Read the full file on GitHub · 228 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 228 lines · 58 tokens per session scan A 1fc4eeab87e7

Subscribe to this mod's changes

claude-agent-sdk-python-expert is an agent published in the GitHub repository nodnarbnitram/claude-code-extensions (16 stars, last pushed 4mo ago), licensed MIT. It adds 58 tokens to every session and 1,629 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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