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Claude Code Subagents Collection

A comprehensive collection of specialized AI subagents for Claude Code, designed to enhance development workflows with domain-specific expertise.

Overview

This repository contains 76 specialized subagents that extend Claude Code's capabilities. Each subagent is an expert in a specific domain, automatically invoked based on context or explicitly called when needed. All agents are configured with specific Claude models based on task complexity for optimal performance and cost-effectiveness.

Available Subagents

Development & Architecture

Language Specialists

Infrastructure & Operations

Quality & Security

Data & AI

Specialized Domains

Documentation

Business & Marketing

SEO & Content Optimization

Model Assignments

All 76 subagents are configured with specific Claude models based on task complexity:

🚀 Haiku (Fast & Cost-Effective) - 15 agents

Model: haiku

⚡ Sonnet (Balanced Performance) - 45 agents

Model: sonnet

Development & Languages:

Infrastructure & Operations: Quality & Support:

🧠 Opus (Maximum Capability) - 15 agents

Model: opus

Installation

These subagents are automatically available when placed in the ~/.claude/agents/ directory.

cd ~/.claude
git clone https://github.com/wshobson/agents.git

Usage

Automatic Invocation

Claude Code will automatically delegate to the appropriate subagent based on the task context and the subagent's description.

Explicit Invocation

Mention the subagent by name in your request: 
"Use the code-reviewer to check my recent changes"
"Have the security-auditor scan for vulnerabilities"
"Get the performance-engineer to optimize this bottleneck"

Usage Examples

Single Agent Tasks

# Code quality and review
"Use code-reviewer to analyze this component for best practices"
"Have code-reviewer scrutinize these configuration changes"
"Have security-auditor check for OWASP compliance issues"
Development tasks  

"Get backend-architect to design a user authentication API"
"Use frontend-developer to create a responsive dashboard layout"
Infrastructure and operations

"Have devops-troubleshooter analyze these production logs"
"Use cloud-architect to design a scalable AWS architecture"
"Get network-engineer to debug SSL certificate issues"
"Use database-admin to set up backup and replication"
Data and AI

"Get data-scientist to analyze this customer behavior dataset"
"Use ai-engineer to build a RAG system for document search"
"Have mlops-engineer set up MLflow experiment tracking"
Business and marketing

"Have business-analyst create investor deck with growth metrics"
"Use content-marketer to write SEO-optimized blog post"
"Get sales-automator to create cold email sequence"
"Have customer-support draft FAQ documentation"

Multi-Agent Workflows

These subagents work together seamlessly, and for more complex orchestrations, you can use the Claude Code Commands collection which provides 52 pre-built slash commands that leverage these subagents in sophisticated workflows.

# Feature development workflow
"Implement user authentication feature"

Automatically uses: backend-architect → frontend-developer → test-automator → security-auditor
Performance optimization workflow  

"Optimize the checkout process performance"

Automatically uses: performance-engineer → database-optimizer → frontend-developer
Production incident workflow

"Debug high memory usage in production"

Automatically uses: incident-responder → devops-troubleshooter → error-detective → performance-engineer
Network connectivity workflow

"Fix intermittent API timeouts"

Automatically uses: network-engineer → devops-troubleshooter → performance-engineer
Database maintenance workflow

"Set up disaster recovery for production database"

Automatically uses: database-admin → database-optimizer → incident-responder
ML pipeline workflow

"Build end-to-end ML pipeline with monitoring"

Automatically uses: mlops-engineer → ml-engineer → data-engineer → performance-engineer
Product launch workflow

"Launch new feature with marketing campaign"

Automatically uses: business-analyst → content-marketer → sales-automator → customer-support

Advanced Workflows with Slash Commands

For more sophisticated multi-subagent orchestration, use the companion Commands repository:

# Complex feature development (8+ subagents)
/full-stack-feature Build user dashboard with real-time analytics
Production incident response (5+ subagents) 

/incident-response Database connection pool exhausted
ML infrastructure setup (6+ subagents)

/ml-pipeline Create recommendation engine with A/B testing
Security-focused implementation (7+ subagents)

/security-hardening Implement OAuth2 with zero-trust architecture

Subagent Format

Each subagent follows this structure: 

---
name: subagent-name
description: When this subagent should be invoked
model: haiku  # Optional - specify which model to use (haiku/sonnet/opus)
tools: tool1, tool2  # Optional - defaults to all tools

System prompt defining the subagent's role and capabilities

Model Configuration

As of Claude Code v1.0.64, subagents can specify which Claude model they should use. This allows for cost-effective task delegation based on complexity:

Available models (using simplified naming as of Claude Code v1.0.64): If no model is specified, the subagent will use the system's default model.

Agent Orchestration Patterns

Claude Code automatically coordinates agents using these common patterns:

Sequential Workflows

User Request → Agent A → Agent B → Agent C → Result
Example: "Build a new API feature"
backend-architect → frontend-developer → test-automator → security-auditor

Parallel Execution

User Request → Agent A + Agent B (simultaneously) → Merge Results
Example: "Optimize application performance" 
performance-engineer + database-optimizer → Combined recommendations

Conditional Branching

User Request → Analysis → Route to appropriate specialist
Example: "Fix this bug"
debugger (analyzes) → Routes to: backend-architect OR frontend-developer OR devops-troubleshooter

Review & Validation

Primary Agent → Review Agent → Final Result
Example: "Implement payment processing"
payment-integration → security-auditor → Validated implementation

When to Use Which Agent

🏗️ Planning & Architecture

🔧 Implementation & Development

🛠️ Operations & Maintenance

📊 Analysis & Optimization

🧪 Quality Assurance

📚 Documentation

💼 Business & Strategy

Best Practices

🎯 Task Delegation

🔄 Multi-Agent Workflows

🎛️ Explicit Control

📈 Optimization

Contributing

To add a new subagent:

Troubleshooting

Common Issues

Agent not being invoked automatically:

Unexpected agent selection: Multiple agents producing conflicting advice: Agent seems to lack context:

Getting Help

If agents aren't working as expected:

License

This project is licensed under the MIT License - see the LICENSE file for details.

Learn More

--- Tranlated By Open Ai Tx | Last indexed: 2025-09-04 ---

Original README: View on GitHub

Translated by OpenAiTx | Last updated: 2025-09-16