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".
Scanned 9/20/2026
Install to Claude Code
npx -y skills add lev-os/agents --skill claude-agent-sdk --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Claude Agent Sdk?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/lev-os-claude-agent-sdk)More formats (shields.io, HTML) on the badges page.
---
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.
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!