--- name: claude-agent-sdk description: This skill should be used when building applications with the Claude Agent SDK (Python). Use for creating orchestrators with subagents, configuring agents programmatically, setting up hooks and permissions, and following SDK best practices. Trigger when implementing agentic workflows, multi-agent systems, or SDK-based automation. --- # Claude Agent SDK Build production-ready applications using the Claude Agent SDK for Python. **SDK Version:** This skill targets `claude-agent-sdk>=0.1.6` (Python) ## Overview This skill provides patterns, examples, and best practices for building SDK applications that orchestrate Claude agents. ## Quick Start Copy the template and customize: ```bash cp assets/sdk-template.py my-app.py # Edit my-app.py - customize agents and workflow chmod +x my-app.py ./my-app.py ``` The template includes proper uv script headers, agent definitions, and async patterns. ## Choosing Between query() and ClaudeSDKClient The SDK provides two ways to interact with Claude: the `query()` function for simple one-shot tasks, and `ClaudeSDKClient` for continuous conversations. ### Quick Comparison | Feature | `query()` | `ClaudeSDKClient` | |---------|-----------|-------------------| | **Conversation memory** | No - each call is independent | Yes - maintains context across queries | | **Use case** | One-off tasks, single questions | Multi-turn conversations, complex workflows | | **Complexity** | Simple - one function call | More setup - context manager pattern | | **Hooks support** | No | Yes | | **Custom tools** | No | Yes | | **Interrupts** | No | Yes - can interrupt ongoing operations | | **Session control** | New session each time | Single persistent session | > **Important:** Hooks and custom tools (SDK MCP servers) are **only supported with `ClaudeSDKClient`**, not with `query()`. If you need hooks or custom tools, you must use `ClaudeSDKClient`. > > **Note on Async Runtimes:** The SDK works with both `asyncio` and `anyio`. The official SDK examples prefer `anyio.run()` for better async library compatibility, but `asyncio.run()` works equally well. Use whichever fits your project's async runtime. ### When to Use query() Use `query()` for simple, independent tasks where you don't need conversation history: ```python import anyio # or: import asyncio from claude_agent_sdk import query, ClaudeAgentOptions async def analyze_file(): """One-shot file analysis - no conversation needed.""" options = ClaudeAgentOptions( system_prompt="You are a code analyzer", allowed_tools=["Read", "Grep", "Glob"], permission_mode="acceptEdits" ) async for message in query( prompt="Analyze /path/to/file.py for bugs", options=options ): print(message) anyio.run(analyze_file) # or: asyncio.run(analyze_file()) ``` **Best for:** - Single analysis tasks - Independent file operations - Quick questions without follow-up - Scripts that run once and exit **Key limitation:** Each `query()` call creates a new session with no memory of previous calls. ### When to Use ClaudeSDKClient Use `ClaudeSDKClient` when you need conversation context across multiple interactions: ```python import anyio # or: import asyncio from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions, AssistantMessage, TextBlock async def interactive_debugging(): """Multi-turn debugging conversation with context.""" options = ClaudeAgentOptions( system_prompt="You are a debugging assistant", allowed_tools=["Read", "Grep", "Bash"], permission_mode="acceptEdits" ) async with ClaudeSDKClient(options=options) as client: # First query await client.query("Find all TODO comments in /path/to/project") async for message in client.receive_response(): if isinstance(message, AssistantMessage): for block in message.content: if isinstance(block, TextBlock): print(f"Claude: {block.text}") # Follow-up - Claude remembers the TODOs found above await client.query("Now prioritize them by complexity") async for message in client.receive_response(): if isinstance(message, AssistantMessage): for block in message.content: if isinstance(block, TextBlock): print(f"Claude: {block.text}") # Another follow-up - still in same conversation await client.query("Create a plan to address the top 3") async for message in client.receive_response(): if isinstance(message, AssistantMessage): for block in message.content: if isinstance(block, TextBlock): print(f"Claude: {block.text}") anyio.run(interactive_debugging) # or: asyncio.run(interactive_debugging()) ``` **Best for:** - Multi-turn conversations - Interactive workflows - Tasks requiring context from previous responses - Applications with interrupt capability - Orchestrators managing complex workflows **Key advantage:** Claude remembers all previous queries and responses in the session. **See:** `examples/streaming_mode.py` - Comprehensive ClaudeSDKClient examples with all patterns ### Advanced: Interrupts with ClaudeSDKClient Only `ClaudeSDKClient` supports interrupting ongoing operations: ```python import anyio # or: import asyncio from claude_agent_sdk import ClaudeSDKClient async def interruptible_task(): async with ClaudeSDKClient() as client: await client.query("Run a long analysis on /large/codebase") # Start processing in background async with anyio.create_task_group() as tg: tg.start_soon(process_messages, client) # Simulate user interrupt after 5 seconds await anyio.sleep(5) await client.interrupt() async def process_messages(client): async for message in client.receive_response(): print(message) anyio.run(interruptible_task) # or: asyncio.run(interruptible_task()) ``` ### Quick Decision Guide **Use `query()` if:** - Task is self-contained - No follow-up questions needed - Each execution is independent - Simpler code is preferred **Use `ClaudeSDKClient` if:** - Need conversation memory - Building interactive workflows - Require interrupt capability - Managing complex multi-step processes - Working with orchestrators and subagents ## Core Patterns ### 1. Orchestrator with Subagents Define a main orchestrator that delegates work to specialized subagents. **Critical requirements:** - Orchestrator must use `system_prompt={"type": "preset", "preset": "claude_code"}` (provides Task tool knowledge) - Register agents programmatically via `agents={}` parameter (SDK best practice) - Orchestrator must include `"Task"` in `allowed_tools` - Match agent names exactly between definition and usage **Example:** ```python from claude_agent_sdk import AgentDefinition, ClaudeAgentOptions options = ClaudeAgentOptions( system_prompt={"type": "preset", "preset": "claude_code"}, # REQUIRED for orchestrators allowed_tools=["Bash", "Task", "Read", "Write"], agents={ "analyzer": AgentDefinition( description="Analyzes code structure and patterns", prompt="You are a code analyzer...", tools=["Read", "Grep", "Glob"], model="sonnet" ), "fixer": AgentDefinition( description="Fixes identified issues", prompt="You are a code fixer...", tools=["Read", "Edit", "Bash"], model="sonnet" ) }, permission_mode="acceptEdits", model="claude-sonnet-4-5" ) ``` **See:** - `references/agent-patterns.md` - Complete agent definition patterns - `examples/agents.py` - Official SDK agent examples with different agent types ### 2. System Prompt Configuration Choose the appropriate system prompt pattern: ```python # Orchestrator (use claude_code preset) - dict format (official examples prefer this) system_prompt={"type": "preset", "preset": "claude_code"} # Shorthand format (equivalent, but less explicit) system_prompt="claude_code" # Custom behavior system_prompt="You are a Python expert..." # Extend preset with additional instructions system_prompt={ "type": "preset", "preset": "claude_code", "append": "Additional domain-specific instructions" } ``` **Note:** The shorthand `system_prompt="claude_code"` is equivalent to `{"type": "preset", "preset": "claude_code"}`. Both are valid. Official examples prefer the dict format for explicitness. **See:** - `references/system-prompts.md` - Complete system prompt documentation - `examples/system_prompt.py` - Official SDK system prompt examples ### 3. Tool Restrictions Limit subagent tools to minimum needed: ```python # Read-only analyzer tools=["Read", "Grep", "Glob"] # Code modifier tools=["Read", "Edit", "Bash"] # Test runner tools=["Bash", "Read"] ``` **See:** `references/agent-patterns.md` for common tool combinations ### 4. Hooks Intercept SDK events to control behavior: ```python from claude_agent_sdk import HookMatcher options = ClaudeAgentOptions( hooks={ "PreToolUse": [ HookMatcher(matcher="Bash", hooks=[check_bash_command]) ], "PostToolUse": [ HookMatcher(matcher="Bash", hooks=[review_output]) ] } ) ``` **See:** - `references/hooks-guide.md` - Complete hook patterns documentation - `examples/hooks.py` - Official SDK hook examples with all hook types ### 5. Permission Callbacks Fine-grained control over tool usage: ```python async def permission_callback(tool_name, input_data, context): # Allow read operations if tool_name in ["Read", "Grep", "Glob"]: return PermissionResultAllow() # Block dangerous commands if tool_name == "Bash" and "rm -rf" in input_data.get("command", ""): return PermissionResultDeny(message="Dangerous command") return PermissionResultAllow() options = ClaudeAgentOptions( can_use_tool=permission_callback, permission_mode="default" ) ``` **See:** - `references/tool-permissions.md` - Complete permission patterns and decision guide - `examples/tool_permission_callback.py` - Official SDK permission callback example ## Workflow Templates ### Building an Orchestrator Follow these steps to build an effective orchestrator: **1. Define agent purposes** - What specialized tasks need delegation? - What tools does each agent need? - What constraints should apply? **2. Create agent definitions** ```python agents={ "agent-name": AgentDefinition( description="When to use this agent", prompt="Agent's role and behavior", tools=["Tool1", "Tool2"], model="sonnet" ) } ``` **3. Configure orchestrator** ```python options = ClaudeAgentOptions( system_prompt={"type": "preset", "preset": "claude_code"}, # CRITICAL allowed_tools=["Bash", "Task", "Read", "Write"], agents=agents, permission_mode="acceptEdits" ) ``` **4. Implement workflow** ```python async with ClaudeSDKClient(options=options) as client: await client.query("Use 'agent-name' to perform task") async for message in client.receive_response(): # Process responses pass ``` **See:** `examples/basic-orchestrator.py` for complete working example ### Loading Agents from Files While programmatic registration is recommended, agent content can be stored in markdown files: ```python import yaml def load_agent_definition(path: str) -> AgentDefinition: """Load agent from markdown file with YAML frontmatter.""" with open(path) as f: content = f.read() parts = content.split("---") frontmatter = yaml.safe_load(parts[1]) prompt = parts[2].strip() # Parse tools (comma-separated string or array) tools = frontmatter.get("tools", []) if isinstance(tools, str): tools = [t.strip() for t in tools.split(",")] return AgentDefinition( description=frontmatter["description"], prompt=prompt, tools=tools, model=frontmatter.get("model", "inherit") ) # Load and register programmatically agent = load_agent_definition(".claude/agents/my-agent.md") options = ClaudeAgentOptions(agents={"my-agent": agent}) ``` **See:** `references/agent-patterns.md` for complete loading pattern ## Common Anti-Patterns Avoid these common mistakes: **❌ Missing orchestrator system prompt** ```python # Orchestrator won't know how to use Task tool options = ClaudeAgentOptions(agents={...}) ``` **✅ Correct orchestrator configuration** ```python options = ClaudeAgentOptions( system_prompt="claude_code", agents={...} ) ``` **❌ Mismatched agent names** ```python agents={"investigator": AgentDefinition(...)} await client.query("Use 'markdown-investigator'...") # Wrong name ``` **✅ Exact name matching** ```python agents={"investigator": AgentDefinition(...)} await client.query("Use 'investigator'...") # Matches ``` **❌ Tool/prompt mismatch** ```python system_prompt="Fix bugs you find" allowed_tools=["Read", "Grep"] # Can't fix, only read ``` **✅ Aligned tools and behavior** ```python system_prompt="Analyze code for bugs" allowed_tools=["Read", "Grep", "Glob"] ``` **See:** `references/best-practices.md` for complete anti-patterns list ## Resources ### references/ In-depth documentation loaded as needed: - `api-reference.md` - Complete Python SDK API reference (types, functions, examples) - `agent-patterns.md` - Agent definition patterns, tool restrictions, best practices - `subagents.md` - Comprehensive subagent patterns and SDK integration - `system-prompts.md` - System prompt configuration (preset, custom, append) - `hooks-guide.md` - Hook patterns for all hook types with examples - `tool-permissions.md` - Permission callback patterns and examples - `best-practices.md` - SDK best practices, anti-patterns, debugging tips - `custom-tools.md` - Creating custom tools with SDK MCP servers (Python-only) - `sessions.md` - Session management and resumption patterns (Python-only) - `skills.md` - Using Agent Skills with the SDK (Python-only) - `slash-commands.md` - Slash commands and custom command creation (Python-only) ### examples/ Ready-to-run code examples from official SDK: **Getting Started:** - `quick_start.py` - Basic query() usage and message handling (start here!) - `basic-orchestrator.py` - Complete orchestrator with analyzer and fixer subagents **Core Patterns:** - `agents.py` - Programmatic agent definitions with different agent types - `hooks.py` - Comprehensive hook patterns (PreToolUse, PostToolUse, UserPromptSubmit, etc.) - `system_prompt.py` - System prompt patterns (preset, custom, append) - `streaming_mode.py` - Complete ClaudeSDKClient patterns with multi-turn conversations **Advanced Features:** - `mcp_calculator.py` - Custom tools with SDK MCP server (in-process tool server) - `tool_permission_callback.py` - Permission callbacks with logging and control - `setting_sources.py` - Settings isolation and loading (user/project/local) - `plugin_example.py` - Using plugins with the SDK (relevant for plugin marketplace!) ### assets/ Templates and validation tools: - `sdk-template.py` - Project template with uv script headers and agent structure - `sdk-validation-checklist.md` - Comprehensive checklist for validating SDK applications against best practices ## When to Use This Skill Use this skill when: - Creating new Claude Agent SDK applications - Building orchestrators with multiple subagents - Implementing programmatic agent definitions - Configuring hooks or permission callbacks - Validating/reviewing SDK code (use `assets/sdk-validation-checklist.md`) - Migrating from filesystem agent discovery to programmatic registration - Debugging SDK applications (agent not found, Task tool not working) - Following SDK best practices Do not use for: - Claude Code slash commands or skills (different system) - Direct API usage without SDK - Non-Python implementations (TypeScript SDK has different patterns) ## Next Steps ### For Beginners 1. Start with `examples/quick_start.py` - Learn basic query() usage 2. Try `assets/sdk-template.py` - Template for new projects 3. Review `examples/basic-orchestrator.py` - See orchestrator pattern ### For Intermediate Users 1. Explore core patterns: - `examples/agents.py` - Agent definitions - `examples/system_prompt.py` - System prompt patterns - `examples/streaming_mode.py` - Multi-turn conversations - `examples/hooks.py` - Hook patterns ### For Advanced Users 1. Study advanced features: - `examples/tool_permission_callback.py` - Permission control - `examples/mcp_calculator.py` - Custom tools - `examples/setting_sources.py` - Settings management - `examples/plugin_example.py` - Plugin integration ### Validation & Quality 1. Validate your code with `assets/sdk-validation-checklist.md` 2. Review against best practices in `references/best-practices.md` ### Reference Documentation 1. Consult `references/` as needed for detailed patterns