Claude Agent SDK - Python Expert

Build production-ready AI agents using Anthropic's Claude Agent SDK.

Quick Start

from claude_agent_sdk import query, ClaudeAgentOptions
import asyncio

async def main():
    options = ClaudeAgentOptions(
        allowed_tools=["Read", "Write", "Bash"],
        permission_mode="acceptEdits"
    )
    async for message in query(prompt="Create hello.py", options=options):
        print(message)

asyncio.run(main())

The Agent Loop (GTVR)

All Claude agents follow this pattern:

1. Gather Context - Search files, read docs, query APIs
2. Take Action - Execute tools, write code, run commands
3. Verify Work - Check outputs, self-correct errors
4. Repeat - Iterate until task complete

For detailed patterns: See architecture-patterns.md

Core APIs

Two Interaction Patterns

Pattern	Use Case	State
query()	One-shot tasks, serverless	Stateless
ClaudeSDKClient	Multi-turn conversations	Stateful

query() - Stateless Operations

from claude_agent_sdk import query, ClaudeAgentOptions, ResultMessage

async for message in query(
    prompt="Analyze this codebase",
    options=ClaudeAgentOptions(
        allowed_tools=["Read", "Grep"],
        max_turns=5
    )
):
    if isinstance(message, ResultMessage):
        print(f"Cost: ${message.total_cost_usd:.4f}")

ClaudeSDKClient - Stateful Sessions

from claude_agent_sdk import ClaudeSDKClient

async with ClaudeSDKClient() as client:
    await client.query("What's in this repo?")
    async for msg in client.receive_response():
        print(msg)

    # Follow-up with preserved context
    await client.query("Show me the main entry point")
    async for msg in client.receive_response():
        print(msg)

For complete API reference: See python-sdk.md

Streaming vs Single Mode

Aspect	Streaming	Single
Use Case	Interactive sessions	Serverless, one-shot
Feedback	Real-time	Final only
Interruption	Supported	Not available
Hooks	Full support	Not available

For patterns and examples: See streaming.md

Custom Tools

@tool Decorator

from claude_agent_sdk import tool, create_sdk_mcp_server, ClaudeAgentOptions
from typing import Any

@tool("greet", "Greet a user", {"name": str})
async def greet(args: dict[str, Any]) -> dict[str, Any]:
    return {
        "content": [{"type": "text", "text": f"Hello, {args['name']}!"}]
    }

server = create_sdk_mcp_server(name="tools", tools=[greet])
options = ClaudeAgentOptions(
    mcp_servers={"tools": server},
    allowed_tools=["mcp__tools__greet"]
)

For tool design and MCP integration: See tools-mcp.md

Hooks System

Intercept tool execution for validation, logging, or blocking:

from claude_agent_sdk import ClaudeAgentOptions, HookMatcher, HookContext
from typing import Any

async def validate_bash(
    input_data: dict[str, Any],
    tool_use_id: str | None,
    context: HookContext
) -> dict[str, Any]:
    command = input_data.get("tool_input", {}).get("command", "")
    if "rm -rf" in command:
        return {
            "hookSpecificOutput": {
                "hookEventName": "PreToolUse",
                "permissionDecision": "deny",
                "permissionDecisionReason": "Dangerous command blocked"
            }
        }
    return {}

options = ClaudeAgentOptions(
    hooks={"PreToolUse": [HookMatcher(matcher="Bash", hooks=[validate_bash])]}
)

Hook events: PreToolUse, PostToolUse, UserPromptSubmit, Stop, SubagentStop, PreCompact

Permission Modes

Mode	Behavior
default	Prompt for each action
acceptEdits	Auto-approve file edits
bypassPermissions	Fully autonomous

Authentication

Two authentication methods are supported:

Method	Billing	Use Case
API Key	Per-token	Serverless, CI/CD, production
Subscription	Flat rate	Development, interactive sessions

API Key

options = ClaudeAgentOptions(
    env={"ANTHROPIC_API_KEY": "sk-ant-api..."},
)

Subscription (OAuth)

First authenticate via CLI: claude setup-token

Then force OAuth by clearing any inherited API key:

options = ClaudeAgentOptions(
    env={"ANTHROPIC_API_KEY": ""},  # Empty string forces OAuth
)

The SDK spawns a persistent Claude CLI subprocess that:

• Reads credentials from ~/.claude/.credentials.json once at startup
• Handles token refresh internally using the refreshToken
• Your application does not manage token refresh

For complete auth patterns and token lifecycle: See authentication.md

ClaudeAgentOptions

Key configuration fields:

ClaudeAgentOptions(
    allowed_tools=["Read", "Write", "Bash"],
    permission_mode="acceptEdits",
    system_prompt="You are a coding assistant.",
    max_turns=10,
    max_budget_usd=5.0,
    cwd="/path/to/project",
    mcp_servers={"tools": server},
    hooks={"PreToolUse": [...]},
    setting_sources=["project"]  # Load CLAUDE.md
)

Built-in Tools

Tool	Purpose
Read	Read file contents
Write	Write file contents
Edit	Edit existing files
Bash	Execute shell commands
Glob	Find files by pattern
Grep	Search file contents
WebSearch	Search the web
WebFetch	Fetch URL content
Task	Spawn subagents

Message Types

from claude_agent_sdk import (
    AssistantMessage,  # Claude's response
    UserMessage,       # User input
    SystemMessage,     # System events
    ResultMessage,     # Completion with cost
    TextBlock,         # Text content
    ToolUseBlock,      # Tool invocation
    ToolResultBlock    # Tool output
)

Error Handling

from claude_agent_sdk import (
    ClaudeSDKError,     # Base exception
    CLINotFoundError,   # SDK not installed
    ProcessError,       # Process failure
    CLIJSONDecodeError  # Parse error
)

Production Patterns

• Use allowlists, not denylists for tools
• Implement PreToolUse hooks for validation
• Add PostToolUse hooks for logging
• Set max_turns and max_budget_usd limits
• Use permission_mode="acceptEdits" for development
• Mask secrets in logs

For deployment checklist: See architecture-patterns.md

Reference Files

• python-sdk.md - Complete Python API reference
• streaming.md - Streaming vs single mode patterns
• tools-mcp.md - Tool design and MCP integration
• authentication.md - API key vs subscription, token lifecycle
• architecture-patterns.md - GTVR, orchestration, production

Examples

Complete, runnable scripts demonstrating SDK patterns:

Example	Purpose	Key Patterns
basic_query.py	Simplest working agent	query(), message handling, error handling
custom_tools.py	Custom MCP tools	@tool decorator, create_sdk_mcp_server
stateful_client.py	Production patterns	ClaudeSDKClient, hooks, multi-turn
extended_thinking.py	Extended thinking	ThinkingBlock, max_thinking_tokens
streaming_events.py	Real-time streaming	StreamEvent, include_partial_messages

All examples require claude-agent-sdk>=0.1.20 and the Claude Code CLI.

External Resources

• Context7: Use mcp__context7__get-library-docs with /anthropics/claude-agent-sdk-python
• Archon RAG: Search rag_search_knowledge_base(query="Claude Agent SDK")
• Platform Docs: https://platform.claude.com/docs/en/agent-sdk/python

When to Use This Skill

Use for:

• Building custom agents with Claude Agent SDK
• Designing effective tools and MCP servers
• Implementing permission models and guardrails
• Configuring authentication (API key or subscription)
• Managing token lifecycle and environment variables
• Creating multi-agent orchestration systems
• Deploying agents to production

Not for:

• Basic chat completion (use Messages API)
• Simple API calls (use direct HTTP)
• Non-agentic workflows (use prompts)