agents/README.md

# Claude Code Subagents Collection

A comprehensive collection of 78 specialized AI subagents for [Claude Code](https://docs.anthropic.com/en/docs/claude-code), providing domain-specific expertise across software development, infrastructure, and business operations.

## Overview

This repository provides production-ready subagents that extend Claude Code's capabilities with specialized knowledge. Each subagent incorporates:

- Current industry best practices and standards (2024/2025)
- Production-ready patterns and enterprise architectures
- Deep domain expertise with 8-12 capability areas per agent
- Modern technology stacks and frameworks
- Optimized model selection based on task complexity

## Agent Categories

### Architecture & System Design

#### Core Architecture
- **[backend-architect](backend-architect.md)** - RESTful API design, microservice boundaries, database schemas
- **[frontend-developer](frontend-developer.md)** - React components, responsive layouts, client-side state management
- **[graphql-architect](graphql-architect.md)** - GraphQL schemas, resolvers, federation architecture
- **[architect-reviewer](architect-review.md)** - Architectural consistency analysis and pattern validation
- **[cloud-architect](cloud-architect.md)** - AWS/Azure/GCP infrastructure design and cost optimization
- **[hybrid-cloud-architect](hybrid-cloud-architect.md)** - Multi-cloud strategies across cloud and on-premises environments
- **[kubernetes-architect](kubernetes-architect.md)** - Cloud-native infrastructure with Kubernetes and GitOps

#### UI/UX & Mobile
- **[ui-ux-designer](ui-ux-designer.md)** - Interface design, wireframes, design systems
- **[ui-visual-validator](ui-visual-validator.md)** - Visual regression testing and UI verification
- **[mobile-developer](mobile-developer.md)** - React Native and Flutter application development
- **[ios-developer](ios-developer.md)** - Native iOS development with Swift/SwiftUI
- **[flutter-expert](flutter-expert.md)** - Advanced Flutter development with state management

### Programming Languages

#### Systems & Low-Level
- **[c-pro](c-pro.md)** - System programming with memory management and OS interfaces
- **[cpp-pro](cpp-pro.md)** - Modern C++ with RAII, smart pointers, STL algorithms
- **[rust-pro](rust-pro.md)** - Memory-safe systems programming with ownership patterns
- **[golang-pro](golang-pro.md)** - Concurrent programming with goroutines and channels

#### Web & Application
- **[javascript-pro](javascript-pro.md)** - Modern JavaScript with ES6+, async patterns, Node.js
- **[typescript-pro](typescript-pro.md)** - Advanced TypeScript with type systems and generics
- **[python-pro](python-pro.md)** - Python development with advanced features and optimization
- **[ruby-pro](ruby-pro.md)** - Ruby with metaprogramming, Rails patterns, gem development
- **[php-pro](php-pro.md)** - Modern PHP with frameworks and performance optimization

#### Enterprise & JVM
- **[java-pro](java-pro.md)** - Modern Java with streams, concurrency, JVM optimization
- **[scala-pro](scala-pro.md)** - Enterprise Scala with functional programming and distributed systems
- **[csharp-pro](csharp-pro.md)** - C# development with .NET frameworks and patterns

#### Specialized Platforms
- **[elixir-pro](elixir-pro.md)** - Elixir with OTP patterns and Phoenix frameworks
- **[unity-developer](unity-developer.md)** - Unity game development and optimization
- **[minecraft-bukkit-pro](minecraft-bukkit-pro.md)** - Minecraft server plugin development
- **[sql-pro](sql-pro.md)** - Complex SQL queries and database optimization

### Infrastructure & Operations

#### DevOps & Deployment
- **[devops-troubleshooter](devops-troubleshooter.md)** - Production debugging, log analysis, deployment troubleshooting
- **[deployment-engineer](deployment-engineer.md)** - CI/CD pipelines, containerization, cloud deployments
- **[terraform-specialist](terraform-specialist.md)** - Infrastructure as Code with Terraform modules and state management
- **[dx-optimizer](dx-optimizer.md)** - Developer experience optimization and tooling improvements

#### Database Management
- **[database-optimizer](database-optimizer.md)** - Query optimization, index design, migration strategies
- **[database-admin](database-admin.md)** - Database operations, backup, replication, monitoring

#### Incident Response & Network
- **[incident-responder](incident-responder.md)** - Production incident management and resolution
- **[network-engineer](network-engineer.md)** - Network debugging, load balancing, traffic analysis

### Quality Assurance & Security

#### Code Quality & Review
- **[code-reviewer](code-reviewer.md)** - Code review with security focus and production reliability
- **[security-auditor](security-auditor.md)** - Vulnerability assessment and OWASP compliance
- **[architect-reviewer](architect-review.md)** - Architectural consistency and pattern validation

#### Testing & Debugging
- **[test-automator](test-automator.md)** - Comprehensive test suite creation (unit, integration, e2e)
- **[tdd-orchestrator](tdd-orchestrator.md)** - Test-Driven Development methodology guidance
- **[debugger](debugger.md)** - Error resolution and test failure analysis
- **[error-detective](error-detective.md)** - Log analysis and error pattern recognition

#### Performance & Research
- **[performance-engineer](performance-engineer.md)** - Application profiling and optimization
- **[search-specialist](search-specialist.md)** - Advanced web research and information synthesis

### Data & AI

#### Data Engineering & Analytics
- **[data-scientist](data-scientist.md)** - Data analysis, SQL queries, BigQuery operations
- **[data-engineer](data-engineer.md)** - ETL pipelines, data warehouses, streaming architectures

#### Machine Learning & AI
- **[ai-engineer](ai-engineer.md)** - LLM applications, RAG systems, prompt pipelines
- **[ml-engineer](ml-engineer.md)** - ML pipelines, model serving, feature engineering
- **[mlops-engineer](mlops-engineer.md)** - ML infrastructure, experiment tracking, model registries
- **[prompt-engineer](prompt-engineer.md)** - LLM prompt optimization and engineering

### Documentation & Technical Writing

- **[docs-architect](docs-architect.md)** - Comprehensive technical documentation generation
- **[api-documenter](api-documenter.md)** - OpenAPI/Swagger specifications and developer docs
- **[reference-builder](reference-builder.md)** - Technical references and API documentation
- **[tutorial-engineer](tutorial-engineer.md)** - Step-by-step tutorials and educational content
- **[mermaid-expert](mermaid-expert.md)** - Diagram creation (flowcharts, sequences, ERDs)

### Business & Operations

#### Business Analysis & Finance
- **[business-analyst](business-analyst.md)** - Metrics analysis, reporting, KPI tracking
- **[quant-analyst](quant-analyst.md)** - Financial modeling, trading strategies, market analysis
- **[risk-manager](risk-manager.md)** - Portfolio risk monitoring and management

#### Marketing & Sales
- **[content-marketer](content-marketer.md)** - Blog posts, social media, email campaigns
- **[sales-automator](sales-automator.md)** - Cold emails, follow-ups, proposal generation

#### Support & Legal
- **[customer-support](customer-support.md)** - Support tickets, FAQ responses, customer communication
- **[hr-pro](hr-pro.md)** - HR operations, policies, employee relations
- **[legal-advisor](legal-advisor.md)** - Privacy policies, terms of service, legal documentation

### Specialized Domains

- **[payment-integration](payment-integration.md)** - Payment processor integration (Stripe, PayPal)
- **[legacy-modernizer](legacy-modernizer.md)** - Legacy code refactoring and modernization
- **[context-manager](context-manager.md)** - Multi-agent context management

### SEO & Content Optimization

- **[seo-content-auditor](seo-content-auditor.md)** - Content quality analysis, E-E-A-T signals assessment
- **[seo-meta-optimizer](seo-meta-optimizer.md)** - Meta title and description optimization
- **[seo-keyword-strategist](seo-keyword-strategist.md)** - Keyword analysis and semantic variations
- **[seo-structure-architect](seo-structure-architect.md)** - Content structure and schema markup
- **[seo-snippet-hunter](seo-snippet-hunter.md)** - Featured snippet formatting
- **[seo-content-refresher](seo-content-refresher.md)** - Content freshness analysis
- **[seo-cannibalization-detector](seo-cannibalization-detector.md)** - Keyword overlap detection
- **[seo-authority-builder](seo-authority-builder.md)** - E-E-A-T signal analysis
- **[seo-content-writer](seo-content-writer.md)** - SEO-optimized content creation
- **[seo-content-planner](seo-content-planner.md)** - Content planning and topic clusters

## Model Configuration

Agents are assigned to specific Claude models based on task complexity and computational requirements. The system uses three model tiers:

### Haiku Model (Fast Response) - 11 agents
Optimized for quick, focused tasks with minimal computational overhead:
- `context-manager`, `reference-builder`, `sales-automator`, `search-specialist`
- SEO agents: `seo-meta-optimizer`, `seo-keyword-strategist`, `seo-structure-architect`, `seo-snippet-hunter`, `seo-content-refresher`, `seo-cannibalization-detector`, `seo-content-planner`

### Sonnet Model (Balanced Performance) - 46 agents
Standard model for development and specialized tasks:
- Language specialists (18): All programming language agents
- Frontend/UI agents (5): `frontend-developer`, `ui-ux-designer`, `ui-visual-validator`, `mobile-developer`, `ios-developer`
- Infrastructure agents (14): DevOps, database, network, and deployment specialists
- Quality/Testing agents (4): `test-automator`, `tdd-orchestrator`, `debugger`, `error-detective`
- Data/ML agents (5): Basic ML and data engineering tasks

### Opus Model (Maximum Capability) - 21 agents
Reserved for complex reasoning and critical analysis:
- Architecture & Design (7): `architect-reviewer`, `backend-architect`, `cloud-architect`, `hybrid-cloud-architect`, `kubernetes-architect`, `graphql-architect`, `terraform-specialist`
- Critical Analysis (5): `code-reviewer`, `security-auditor`, `performance-engineer`, `incident-responder`, `database-optimizer`
- AI/ML Complex (5): `ai-engineer`, `ml-engineer`, `mlops-engineer`, `data-scientist`, `prompt-engineer`
- Business Critical (4): `docs-architect`, `hr-pro`, `legal-advisor`, `quant-analyst`

## Installation

Clone the repository to the Claude agents directory:

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

The subagents will be automatically available to Claude Code once placed in the `~/.claude/agents/` directory.

## Usage

### Automatic Delegation
Claude Code automatically selects the appropriate subagent based on task context and requirements. The system analyzes your request and delegates to the most suitable specialist.

### Explicit Invocation
Specify a subagent by name to use a particular specialist:

```
"Use code-reviewer to analyze the recent changes"
"Have security-auditor scan for vulnerabilities"
"Get performance-engineer to optimize this bottleneck"
```

## Usage Examples

### Code Quality & Security
```
code-reviewer: Analyze component for best practices
security-auditor: Check for OWASP compliance
tdd-orchestrator: Implement feature with test-first approach
performance-engineer: Profile and optimize bottlenecks
```

### Development & Architecture
```
backend-architect: Design authentication API
frontend-developer: Create responsive dashboard
graphql-architect: Design federated GraphQL schema
mobile-developer: Build cross-platform mobile app
```

### Infrastructure & Operations
```
devops-troubleshooter: Analyze production logs
cloud-architect: Design scalable AWS architecture
network-engineer: Debug SSL certificate issues
database-admin: Configure backup and replication
terraform-specialist: Write infrastructure modules
```

### Data & Machine Learning
```
data-scientist: Analyze customer behavior dataset
ai-engineer: Build RAG system for document search
mlops-engineer: Set up experiment tracking
ml-engineer: Deploy model to production
```

### Business & Documentation
```
business-analyst: Create metrics dashboard
docs-architect: Generate technical documentation
api-documenter: Write OpenAPI specifications
content-marketer: Create SEO-optimized content
```

## Multi-Agent Workflows

Subagents coordinate automatically for complex tasks. The system intelligently sequences multiple specialists based on task requirements.

### Common Workflow Patterns

**Feature Development**
```
"Implement user authentication"
→ backend-architect → frontend-developer → test-automator → security-auditor
```

**Performance Optimization**
```
"Optimize checkout process"
→ performance-engineer → database-optimizer → frontend-developer
```

**Production Incidents**
```
"Debug high memory usage"
→ incident-responder → devops-troubleshooter → error-detective → performance-engineer
```

**Infrastructure Setup**
```
"Set up disaster recovery"
→ database-admin → database-optimizer → terraform-specialist
```

**ML Pipeline Development**
```
"Build ML pipeline with monitoring"
→ mlops-engineer → ml-engineer → data-engineer → performance-engineer
```

### Integration with Claude Code Commands

For sophisticated multi-agent orchestration, use the [Claude Code Commands](https://github.com/wshobson/commands) collection which provides 52 pre-built slash commands:

```
/full-stack-feature   # Coordinates 8+ agents for complete feature development
/incident-response    # Activates incident management workflow
/ml-pipeline         # Sets up end-to-end ML infrastructure
/security-hardening  # Implements security best practices across stack
```

## Subagent Format

Each subagent is defined as a Markdown file with frontmatter:

```markdown
---
name: subagent-name
description: Activation criteria for this subagent
model: haiku|sonnet|opus  # Optional: Model selection
tools: tool1, tool2       # Optional: Tool restrictions
---

System prompt defining the subagent's expertise and behavior
```

### Model Selection Criteria

- **haiku**: Simple, deterministic tasks with minimal reasoning
- **sonnet**: Standard development and engineering tasks
- **opus**: Complex analysis, architecture, and critical operations

## Agent Orchestration Patterns

### Sequential Processing
Agents execute in sequence, passing context forward:
```
backend-architect → frontend-developer → test-automator → security-auditor
```

### Parallel Execution
Multiple agents work simultaneously on different aspects:
```
performance-engineer + database-optimizer → Merged analysis
```

### Conditional Routing
Dynamic agent selection based on analysis:
```
debugger → [backend-architect | frontend-developer | devops-troubleshooter]
```

### Validation Pipeline
Primary work followed by specialized review:
```
payment-integration → security-auditor → Validated implementation
```

## Agent Selection Guide

### Architecture & Planning
- `backend-architect`: API design, microservices, database schemas
- `cloud-architect`: Infrastructure design, scalability planning
- `ui-ux-designer`: Interface design, wireframes, design systems

### Development by Language
- Systems: `c-pro`, `cpp-pro`, `rust-pro`, `golang-pro`
- Web: `javascript-pro`, `typescript-pro`, `python-pro`, `ruby-pro`, `php-pro`
- Enterprise: `java-pro`, `csharp-pro`, `scala-pro`
- Mobile: `ios-developer`, `flutter-expert`, `mobile-developer`
- Specialized: `elixir-pro`, `unity-developer`, `minecraft-bukkit-pro`

### Operations & Infrastructure
- `devops-troubleshooter`: Production issues, deployment problems
- `incident-responder`: Critical outages and immediate response
- `database-optimizer`: Query performance, indexing strategies
- `database-admin`: Backup, replication, disaster recovery
- `terraform-specialist`: Infrastructure as Code
- `network-engineer`: Network debugging, load balancing

### Quality & Security
- `code-reviewer`: Code quality and security analysis
- `security-auditor`: Vulnerability scanning, compliance
- `test-automator`: Test suite creation and strategy
- `performance-engineer`: Application optimization
- `debugger`: Bug investigation and resolution

### Data & Machine Learning
- `data-scientist`: Data analysis and insights
- `ai-engineer`: LLM applications and RAG systems
- `ml-engineer`: Model development and deployment
- `mlops-engineer`: ML infrastructure and pipelines

### Documentation & Business
- `docs-architect`: Technical documentation generation
- `api-documenter`: OpenAPI specifications
- `business-analyst`: Metrics and reporting
- `legal-advisor`: Legal documentation and compliance

## Best Practices

### Task Delegation
1. **Automatic selection** - Let Claude Code analyze context and select optimal agents
2. **Clear requirements** - Specify constraints, tech stack, and quality standards
3. **Trust specialization** - Each agent is optimized for their specific domain

### Multi-Agent Workflows
1. **High-level requests** - Allow agents to coordinate complex multi-step tasks
2. **Context preservation** - Ensure agents have necessary background information
3. **Integration review** - Verify how different agents' outputs work together

### Explicit Control
1. **Direct invocation** - Specify agents when you need particular expertise
2. **Strategic combination** - Use multiple specialists for validation
3. **Review patterns** - Request specific review workflows (e.g., "security-auditor reviews API design")

### Performance Optimization
1. **Monitor effectiveness** - Track which agents work best for your use cases
2. **Iterative refinement** - Use agent feedback to improve requirements
3. **Complexity matching** - Align task complexity with agent capabilities

## Contributing

To add a new subagent:

1. Create a new `.md` file with appropriate frontmatter
2. Use lowercase, hyphen-separated naming convention
3. Write clear activation criteria in the description
4. Define comprehensive system prompt with expertise areas

## Troubleshooting

### Agent Not Activating
- Ensure request clearly indicates the domain
- Be specific about task type and requirements
- Use explicit invocation if automatic selection fails

### Unexpected Agent Selection
- Provide more context about tech stack
- Include specific requirements in request
- Use direct agent naming for precise control

### Conflicting Recommendations
- Normal behavior - specialists have different priorities
- Request reconciliation between specific agents
- Consider trade-offs based on project requirements

### Missing Context
- Include background information in requests
- Reference previous work or patterns
- Provide project-specific constraints

## License

MIT License - see [LICENSE](LICENSE) file for details.

## Resources

- [Claude Code Documentation](https://docs.anthropic.com/en/docs/claude-code)
- [Subagents Documentation](https://docs.anthropic.com/en/docs/claude-code/sub-agents)
- [Claude Code GitHub](https://github.com/anthropics/claude-code)
- [Claude Code Commands](https://github.com/wshobson/commands)