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claude-agent-sdk

Guide for building production AI agents with Anthropic's Claude Agent SDK. Use when the user wants to create custom agents, implement automation pipelines, add custom tools, configure subagents, or integrate Claude into existing workflows. Triggers on "build an agent", "claude agent sdk", "create automation", "custom tool", "subagent", or "agent pipeline".

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Repository
lev-os/agents
Letzte Quellaktivität
7. März 2026 um 00:14
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Englisch
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22
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2

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SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
claude-agent-sdk
description
Guide for building production AI agents with Anthropic's Claude Agent SDK. Use when the user wants to create custom agents, implement automation pipelines, add custom tools, configure subagents, or integrate Claude into existing workflows. Triggers on "build an agent", "claude agent sdk", "create automation", "custom tool", "subagent", or "agent pipeline".
version
1.0.0
dependencies
python>=3.10, claude-agent-sdk>=1.0.0
# Claude Agent SDK Build production-ready AI agents using Anthropic's official SDK - the same tools powering Claude Code. ## Quick Decision Tree ``` User wants to build agents? │ ├─→ Simple single-task agent? │ └─→ See "Basic Agent" below │ ├─→ Agent with custom tools? │ └─→ See "Custom Tools (MCP)" below │ ├─→ Multi-agent orchestration? │ └─→ See "Subagents" below │ ├─→ Integrate into existing workflow? │ └─→ See "Integration Patterns" below │ └─→ Need detailed reference? └─→ Load references/api-reference.md ``` ## Installation ```bash # Python pip install claude-agent-sdk # TypeScript npm install @anthropic-ai/claude-agent-sdk ``` **Requirement**: Claude Code must be installed (serves as SDK runtime). ## Basic Agent ```python import asyncio from claude_agent_sdk import query, ClaudeAgentOptions async def main(): async for message in query( prompt="Find and fix the bug in auth.py", options=ClaudeAgentOptions( allowed_tools=["Read", "Edit", "Bash"], permission_mode="acceptEdits" # Auto-approve edits ) ): if hasattr(message, "result"): print(message.result) asyncio.run(main()) ``` ### Built-in Tools No implementation needed - just allow them: | Tool | Purpose | |------|---------| | `Read` | Read files | | `Write` | Create files | | `Edit` | Modify files | | `Bash` | Run commands | | `Glob` | Find files by pattern | | `Grep` | Search file contents | | `WebSearch` | Search the web | | `WebFetch` | Fetch web pages | ### Permission Modes - `standard` - Ask for approval (default) - `acceptEdits` - Auto-approve file changes - `bypassPermissions` - Full autonomy (CI/CD use) ## Custom Tools (MCP) Create in-process MCP servers for custom functionality: ```python from claude_agent_sdk import tool, create_sdk_mcp_server, query, ClaudeAgentOptions @tool("get_weather", "Get temperature for location", {"lat": float, "lon": float}) async def get_weather(args: dict) -> dict: # Your implementation return {"content": [{"type": "text", "text": f"Temperature: 72°F"}]} custom_server = create_sdk_mcp_server( name="my-tools", version="1.0.0", tools=[get_weather] ) async for message in query( prompt="What's the weather in SF?", options=ClaudeAgentOptions( mcp_servers={"my-tools": custom_server}, allowed_tools=["mcp__my-tools__get_weather"] ) ): print(message) ``` **Tool naming**: `mcp__{server_name}__{tool_name}` ## Subagents Delegate tasks to specialized agents: ```python from claude_agent_sdk import query, ClaudeAgentOptions, AgentDefinition async for message in query( prompt="Review auth module for security issues", options=ClaudeAgentOptions( allowed_tools=["Read", "Grep", "Task"], # Task enables subagents agents={ "security-reviewer": AgentDefinition( description="Security code review specialist", prompt="You are a security expert. Find vulnerabilities.", tools=["Read", "Grep", "Glob"], # Read-only model="sonnet" ), "test-runner": AgentDefinition( description="Runs and analyzes tests", prompt="Execute tests and analyze results.", tools=["Bash", "Read"], model="haiku" # Faster for routine tasks ) } ) ): if hasattr(message, "result"): print(message.result) ``` **Best Practice**: One job per subagent. Orchestrator plans and delegates. ## Sessions (Context Persistence) Maintain state across interactions: ```python session_id = None # First query - capture session async for msg in query(prompt="Read the auth module"): if hasattr(msg, 'subtype') and msg.subtype == 'init': session_id = msg.session_id # Resume with full context async for msg in query( prompt="Now find all callers", # "it" understood from context options=ClaudeAgentOptions(resume=session_id) ): print(msg) ``` ## Hooks (Behavior Control) Inject custom logic at key points: ```python from claude_agent_sdk import HookMatcher async def audit_log(input_data, tool_use_id, context): file_path = input_data.get('tool_input', {}).get('file_path') with open('audit.log', 'a') as f: f.write(f"{datetime.now()}: modified {file_path}\n") return {} async for message in query( prompt="Refactor utils.py", options=ClaudeAgentOptions( hooks={ "PostToolUse": [HookMatcher(matcher="Edit|Write", hooks=[audit_log])] } ) ): print(message) ``` **Available hooks**: `PreToolUse`, `PostToolUse`, `SessionStart`, `SessionEnd`, `UserPromptSubmit` ## Integration Patterns ### CI/CD Pipeline ```python async def run_code_review(pr_branch: str): async for msg in query( prompt=f"Review changes in {pr_branch}", options=ClaudeAgentOptions( allowed_tools=["Read", "Glob", "Grep", "Bash"], permission_mode="bypassPermissions" ) ): if hasattr(msg, "result"): return msg.result ``` ### REST API Wrapper ```python from fastapi import FastAPI app = FastAPI() @app.post("/analyze") async def analyze(code_path: str): results = [] async for msg in query( prompt=f"Analyze {code_path}", options=ClaudeAgentOptions(allowed_tools=["Read", "Grep"]) ): if hasattr(msg, "result"): results.append(msg.result) return {"analysis": results} ``` ### External MCP Server ```python async for message in query( prompt="Open example.com and describe it", options=ClaudeAgentOptions( mcp_servers={ "playwright": { "command": "npx", "args": ["@playwright/mcp@latest"] } } ) ): print(message) ``` ## Model Selection | Model | Use Case | |-------|----------| | `opus` | Critical tasks, complex reasoning | | `sonnet` | Balanced performance (default) | | `haiku` | Fast, routine tasks | ## References - **references/api-reference.md** - Complete API documentation - **references/patterns.md** - Production patterns and examples Load references as needed for detailed implementation guidance.
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