{"id":29927129,"url":"https://github.com/lst97/claude-code-sub-agents","last_synced_at":"2026-06-30T17:33:40.563Z","repository":{"id":307411871,"uuid":"1027735852","full_name":"lst97/claude-code-sub-agents","owner":"lst97","description":"Collection of specialized AI subagents for Claude Code for personal use (full-stack development).","archived":false,"fork":false,"pushed_at":"2025-08-12T09:13:33.000Z","size":7304,"stargazers_count":768,"open_issues_count":0,"forks_count":125,"subscribers_count":14,"default_branch":"main","last_synced_at":"2025-08-12T10:27:28.703Z","etag":null,"topics":["ai-agents","claude-code","claudecode-config","claudecode-subagents","sub-agents","subagents"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/lst97.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":"security/security-auditor.md","support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-07-28T13:04:48.000Z","updated_at":"2025-08-12T09:28:24.000Z","dependencies_parsed_at":"2025-07-31T05:48:19.073Z","dependency_job_id":null,"html_url":"https://github.com/lst97/claude-code-sub-agents","commit_stats":null,"previous_names":["lst97/claude-code-sub-agents"],"tags_count":2,"template":false,"template_full_name":null,"purl":"pkg:github/lst97/claude-code-sub-agents","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lst97%2Fclaude-code-sub-agents","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lst97%2Fclaude-code-sub-agents/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lst97%2Fclaude-code-sub-agents/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lst97%2Fclaude-code-sub-agents/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/lst97","download_url":"https://codeload.github.com/lst97/claude-code-sub-agents/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lst97%2Fclaude-code-sub-agents/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":34977668,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-30T02:00:05.919Z","response_time":92,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ai-agents","claude-code","claudecode-config","claudecode-subagents","sub-agents","subagents"],"created_at":"2025-08-02T13:02:02.475Z","updated_at":"2026-06-30T17:33:40.552Z","avatar_url":"https://github.com/lst97.png","language":null,"funding_links":[],"categories":["Others","HarmonyOS","Agent Collections","Claude Code Ecosystem","Source Catalog","Sub Agents","🔹 Claude Code Subagents","Development \u0026 Engineering","Subagent Collections","框架扩展"],"sub_categories":["Windows Manager","Specialized Collections","Agent Collections \u0026 Orchestration","Specialized Development","Specialized Agents"],"readme":"# Claude Code Subagents Collection\n\nA comprehensive collection of 33 specialized AI subagents for [Claude Code](https://docs.anthropic.com/en/docs/claude-code), designed to enhance development workflows with domain-specific expertise and intelligent automation.\n\n## 🚀 Overview\n\nThis repository contains a curated set of specialized subagents that extend Claude Code's capabilities across the entire software development lifecycle. Each subagent is an expert in a specific domain, automatically invoked based on context analysis or explicitly called when specialized expertise is needed.\n\n### Key Features\n\n- **🤖 Intelligent Auto-Delegation**: Claude Code automatically selects optimal agents based on task context\n- **🔧 Domain Expertise**: Each agent specializes in specific technologies, patterns, and best practices\n- **🔄 Multi-Agent Orchestration**: Seamless coordination between agents for complex workflows\n- **📊 Quality Assurance**: Built-in review and validation patterns across all domains\n- **⚡ Performance Optimized**: Agents designed for efficient task completion and resource utilization\n\n## Available Subagents\n\nAgents are now organized into logical categories for easier navigation:\n\n### 🏗️ [Development](agents/development/)\n\n**Frontend \u0026 UI Specialists**\n\n- **[frontend-developer](agents/development/frontend-developer.md)** - Build React components, implement responsive layouts, and handle client-side state management\n- **[ui-designer](agents/development/ui-designer.md)** - Creative UI design focused on user-friendly interfaces\n- **[ux-designer](agents/development/ux-designer.md)** - User experience design and interaction optimization\n- **[react-pro](agents/development/react-pro.md)** - Expert React development with hooks, performance optimization, and best practices\n- **[nextjs-pro](agents/development/nextjs-pro.md)** - Next.js specialist for SSR, SSG, and full-stack React applications\n\n**Backend \u0026 Architecture**\n\n- **[backend-architect](agents/development/backend-architect.md)** - Design RESTful APIs, microservice boundaries, and database schemas\n- **[full-stack-developer](agents/development/full-stack-developer.md)** - End-to-end web application development from UI to database with seamless integration\n\n**Language Specialists**\n\n- **[python-pro](agents/development/python-pro.md)** - Write idiomatic Python code with advanced features and optimizations\n- **[golang-pro](agents/development/golang-pro.md)** - Write idiomatic Go code with goroutines, channels, and interfaces\n- **[typescript-pro](agents/development/typescript-pro.md)** - Advanced TypeScript development with type safety and modern patterns\n\n**Platform \u0026 Mobile**\n\n- **[mobile-developer](agents/development/mobile-developer.md)** - Develop React Native or Flutter apps with native integrations\n- **[electron-pro](agents/development/electorn-pro.md)** - Electron desktop application development and cross-platform solutions\n\n**Developer Experience**\n\n- **[dx-optimizer](agents/development/dx-optimizer.md)** - Developer Experience specialist that improves tooling, setup, and workflows\n- **[legacy-modernizer](agents/development/legacy-modernizer.md)** - Refactor legacy codebases and implement gradual modernization\n\n### ☁️ [Infrastructure](agents/infrastructure/)\n\n- **[cloud-architect](agents/infrastructure/cloud-architect.md)** - Design AWS/Azure/GCP infrastructure and optimize cloud costs\n- **[deployment-engineer](agents/infrastructure/deployment-engineer.md)** - Configure CI/CD pipelines, Docker containers, and cloud deployments\n- **[devops-incident-responder](agents/infrastructure/devops-incident-responder.md)** - Debug production issues, analyze logs, and fix deployment failures\n- **[incident-responder](agents/infrastructure/incident-responder.md)** - Handles production incidents with urgency and precision\n- **[performance-engineer](agents/infrastructure/performance-engineer.md)** - Profile applications, optimize bottlenecks, and implement caching strategies\n\n### 🔍 [Quality \u0026 Testing](agents/quality-testing/)\n\n- **[code-reviewer](agents/quality-testing/code-reviewer.md)** - Expert code review for quality, security, and maintainability\n- **[architect-reviewer](agents/quality-testing/architect-review.md)** - Reviews code changes for architectural consistency and design patterns\n- **[qa-expert](agents/quality-testing/qa-expert.md)** - Comprehensive QA processes and testing strategies for quality assurance\n- **[test-automator](agents/quality-testing/test-automator.md)** - Create comprehensive test suites with unit, integration, and e2e tests\n- **[debugger](agents/quality-testing/debugger.md)** - Debugging specialist for errors, test failures, and unexpected behavior\n\n### 📊 [Data \u0026 AI](agents/data-ai/)\n\n**Data Engineering \u0026 Analytics**\n\n- **[data-engineer](agents/data-ai/data-engineer.md)** - Build ETL pipelines, data warehouses, and streaming architectures\n- **[data-scientist](agents/data-ai/data-scientist.md)** - Data analysis expert for SQL queries, BigQuery operations, and data insights\n- **[database-optimizer](agents/data-ai/database-optimizer.md)** - Optimize SQL queries, design efficient indexes, and handle database migrations\n- **[postgres-pro](agents/data-ai/postgres-pro.md)** - PostgreSQL database expert for advanced queries and optimizations\n- **[graphql-architect](agents/data-ai/graphql-architect.md)** - Design GraphQL schemas, resolvers, and federation patterns\n\n**AI \u0026 Machine Learning**\n\n- **[ai-engineer](agents/data-ai/ai-engineer.md)** - Build LLM applications, RAG systems, and prompt pipelines\n- **[ml-engineer](agents/data-ai/ml-engineer.md)** - Implement ML pipelines, model serving, and feature engineering\n- **[prompt-engineer](agents/data-ai/prompt-engineer.md)** - Optimizes prompts for LLMs and AI systems\n\n### 🛡️ [Security](agents/security/)\n\n- **[security-auditor](agents/security/security-auditor.md)** - Review code for vulnerabilities and ensure OWASP compliance\n\n### 🎯 [Specialization](agents/specialization/)\n\n- **[api-documenter](agents/specialization/api-documenter.md)** - Create OpenAPI/Swagger specs and write developer documentation\n- **[documentation-expert](agents/specialization/documentation-expert.md)** - Professional technical writing and comprehensive documentation systems\n\n### 💼 [Business](agents/business/)\n\n- **[product-manager](agents/business/product-manager.md)** - Strategic product management with roadmap planning and stakeholder alignment\n\n### 🎭 Meta-Orchestration\n\n- **[agent-organizer](agents/agent-organizer.md)** - Master orchestrator for complex, multi-agent tasks. Analyzes project requirements, assembles optimal agent teams, and manages collaborative workflows for comprehensive project execution.\n\n**Key Capabilities:**\n\n- **Intelligent Project Analysis**: Technology stack detection, architecture pattern recognition, and requirement extraction\n- **Strategic Team Assembly**: Selects optimal 1-3 agent teams based on project needs and complexity\n- **Workflow Orchestration**: Manages multi-phase collaboration with quality gates and validation checkpoints\n- **Efficiency Optimization**: Focused teams for common tasks (bug fixes, features, documentation) with comprehensive orchestration for complex projects\n\n**When to Use**: Complex multi-step projects, cross-domain tasks, architecture decisions, comprehensive analysis, or any scenario requiring coordinated expertise from multiple specialized agents.\n\n## 📦 Installation\n\n### Quick Setup\n\n### Manual Installation (Recommend)\n\nAlternatively, you can manually copy individual agent files:\n\n```bash\n# Prevent replacing documents from other providers\nmkdir ~/.claude/agents/lst97\n# Copy specific agents to your Claude agents directory\ncp /path/to/agents/*.md ~/.claude/agents/lst97\n```\n\n### Verification\n\nTo verify agents are loaded correctly:\n\n```bash\n# List all available agents\nls ~/.claude/agents/lst97/*.md\n\n# Check Claude Code recognizes the agents (run in Claude Code)\n# \"List all available subagents\"\n```\n\n### Quick Installation\n\nThese subagents are automatically available when placed in the `~/.claude/agents/` directory. Claude Code will automatically detect and load them on startup. This will enable the CLAUDE.md to be available in global scope, may also conflict with other repository.\n\n```bash\n# Clone the repository to your Claude agents directory\n# Documents are base on the scaffold from https://github.com/wshobson/agents.git\ncd ~/.claude\ngit clone https://github.com/lst97/claude-code-sub-agents.git\n\n# Or if the directory already exists, pull the latest updates\ncd ~/.claude\ngit pull origin main\n```\n\n### 🔧 MCP Server Configuration (Required for Full Performance)\n\nTo enable optimal performance with specialized MCP (Model Context Protocol) servers that enhance agent capabilities, add the following configuration to your **global** Claude settings file (`~/.claude.json`):\n\n```json\n\"mcpServers\": {\n  \"sequential-thinking\": {\n    \"type\": \"stdio\",\n    \"command\": \"npx\",\n    \"args\": [\n      \"-y\",\n      \"@modelcontextprotocol/server-sequential-thinking\"\n    ],\n    \"env\": {}\n  },\n  \"context7\": {\n    \"type\": \"stdio\",\n    \"command\": \"npx\",\n    \"args\": [\n      \"-y\",\n      \"@upstash/context7-mcp\"\n    ],\n    \"env\": {}\n  },\n  \"magic\": {\n    \"type\": \"stdio\",\n    \"command\": \"npx\",\n    \"args\": [\n      \"-y\",\n      \"@21st-dev/magic@latest\",\n      \"API_KEY=\\\"api-key\\\"\" // API key is required\n    ],\n    \"env\": {}\n  },\n  \"playwright\": {\n    \"type\": \"stdio\",\n    \"command\": \"npx\",\n    \"args\": [\n      \"@playwright/mcp@latest\"\n    ],\n    \"env\": {}\n  },\n  \"filesystem\": {\n    \"command\": \"npx\",\n    \"args\": [\n      \"-y\",\n      \"@modelcontextprotocol/server-filesystem\",\n      \"/your/allowed/path\" // please add your path here\n    ]\n  },\n  \"puppeteer\": {\n    \"command\": \"npx\",\n    \"args\": [\n      \"-y\",\n      \"puppeteer-mcp-server\"\n    ],\n    \"env\": {}\n  }\n}\n```\n\n**MCP Server Benefits:**\n\n- **sequential-thinking**: Enhanced multi-step reasoning and complex analysis\n- **context7**: Access to up-to-date documentation and framework patterns\n- **magic**: Advanced UI component generation and design system integration\n- **playwright**: Cross-browser testing and E2E automation capabilities\n\n**Note**: These MCP servers significantly enhance agent capabilities but are not strictly required for basic functionality.\n\n### 🎭 Advanced: Agent-Organizer Auto-Dispatch Setup\n\nFor complex projects requiring multi-agent coordination, you can enable the dispatch protocol in your **project root directory** (not globally):\n\n```bash\n# Copy CLAUDE.md to your PROJECT root directory (recommended)\ncp /path/to/agents/CLAUDE.md /path/to/your/project/CLAUDE.md\n```\n\n**⚠️ Project-Scope Recommendation:**\n\n- **✅ Project-Specific**: Place CLAUDE.md in individual project roots for targeted orchestration\n- **❌ Global Scope**: Avoid placing in `~/.claude/CLAUDE.md` to prevent over-orchestration of simple tasks\n- **🎯 Selective Usage**: Enable only for projects requiring comprehensive multi-agent workflows\n\n**Trade-offs to Consider:**\n\n- **Quality vs Speed**: Multi-agent workflows provide expert results but take longer\n- **Token Efficiency**: 2-5x token usage for comprehensive analysis and implementation\n- **Complexity Matching**: Best for complex projects, may over-engineer simple tasks\n\n## 🔧 Usage\n\n### Automatic Invocation (Recommended)\n\nClaude Code intelligently analyzes your request and automatically delegates to the most appropriate subagent(s) based on:\n\n- **Context Analysis**: Keywords, file types, and project structure\n- **Task Classification**: Development, debugging, optimization, etc.\n- **Domain Expertise**: Matching requirements to specialist knowledge\n- **Workflow Patterns**: Common multi-agent coordination scenarios\n\n**Example**: `\"Implement user authentication with secure password handling\"` → Automatically uses: `backend-architect` → `security-auditor` → `test-automator`\n\n### Explicit Invocation\n\nFor specific expertise or when you want control over agent selection:\n\n```bash\n# Direct agent requests\n\"Use the code-reviewer to check my recent changes\"\n\"Have the security-auditor scan for vulnerabilities\"\n\"Get the performance-engineer to optimize this bottleneck\"\n\n# Multi-agent requests\n\"Have backend-architect design the API, then security-auditor review it\"\n\"Use data-scientist to analyze this dataset, then ai-engineer to build recommendations\"\n```\n\n### Hybrid Approach\n\nCombine automatic and explicit invocation:\n\n```bash\n# Start explicit, let Claude coordinate the rest\n\"Use backend-architect to design a REST API for user management, then handle the implementation automatically\"\n\n# Explicit validation after automatic work\n\"Implement this feature automatically, then have security-auditor review the result\"\n```\n\n## 💡 Usage Examples\n\n### Direct Agent Invocation\n\nWhen not using agent-organizer, specify the exact agent needed for your task:\n\n```bash\n# Development Tasks\n\"Use backend-architect to design a REST API for user management\"\n\"Have frontend-developer create a responsive login form component\"\n\"Get python-pro to implement async data processing with proper error handling\"\n\"Have react-pro optimize this component for performance and add proper TypeScript types\"\n\"Use typescript-pro to refactor this module with advanced type safety\"\n\n# Code Quality \u0026 Review\n\"Use code-reviewer to analyze this pull request for best practices\"\n\"Have architect-reviewer check if this change maintains architectural consistency\"\n\"Get debugger to investigate why this test is failing intermittently\"\n\n# Security \u0026 Performance\n\"Have security-auditor scan this authentication module for vulnerabilities\"\n\"Use performance-engineer to identify bottlenecks in this API endpoint\"\n\"Get database-optimizer to improve these slow queries\"\n\n# Testing \u0026 QA\n\"Use test-automator to create comprehensive tests for this user service\"\n\"Have qa-expert design a testing strategy for this new feature\"\n\n# Infrastructure \u0026 Deployment\n\"Get devops-incident-responder to investigate this production deployment failure\"\n\"Use cloud-architect to design scalable infrastructure for this microservice\"\n\"Have deployment-engineer set up CI/CD pipeline for this repository\"\n\n# Data \u0026 AI\n\"Use data-scientist to analyze user behavior patterns in this dataset\"\n\"Have ai-engineer implement a RAG system for document search\"\n\"Get ml-engineer to deploy this trained model to production\"\n\n# Documentation \u0026 Specialization\n\"Use documentation-expert to create comprehensive API documentation\"\n\"Have api-documenter generate OpenAPI specs for these endpoints\"\n\n# Multi-Agent Coordination Examples\n\"Use backend-architect to design the API, then have security-auditor review it\"\n\"Get frontend-developer to build the component, then use test-automator for coverage\"\n\"Have database-optimizer improve queries, then performance-engineer validate results\"\n```\n\n### Agent Communication Protocol Examples\n\nEach agent uses a standardized communication protocol with agent-specific context requests. Here are examples:\n\n#### Frontend Development\n\n```json\n{\n  \"requesting_agent\": \"frontend-developer\",\n  \"request_type\": \"get_task_briefing\",\n  \"payload\": {\n    \"query\": \"Initial briefing required for UI component development. Provide overview of existing React project structure, design system, component library, and relevant frontend files.\"\n  }\n}\n```\n\n## 📋 Subagent Format\n\nEach subagent follows a standardized structure for consistent behavior and optimal integration:\n\n### File Structure\n\n```markdown\n---\nname: subagent-name\ndescription: When this subagent should be invoked\ntools: tool1, tool2  # Optional - defaults to all tools\n---\n\n# Subagent Name\n\n**Role**: Detailed role description and primary responsibilities\n\n**Expertise**: Specific technologies, frameworks, and domain knowledge\n\n**Key Capabilities**:\n- Capability 1: Description\n- Capability 2: Description\n- Capability 3: Description\n\nSystem prompt defining the subagent's specialized behavior, decision-making patterns, and interaction style with other agents.\n```\n\n### Required Components\n\n- **Name**: Kebab-case filename matching the agent name\n- **Description**: Clear trigger conditions for automatic invocation\n- **Role Definition**: Specific responsibilities and boundaries\n- **Expertise Areas**: Technologies, patterns, and domain knowledge\n- **System Prompt**: Detailed instructions for specialized behavior\n\n### Optional Components\n\n- **Tools**: Specific Claude Code tools (defaults to all available tools)\n- **Dependencies**: Other agents this one commonly works with\n- **Patterns**: Common workflow patterns and coordination scenarios\n\n## 🔄 Agent Orchestration Patterns\n\nClaude Code automatically coordinates agents using these patterns:\n\n- **Sequential**: `architect → implement → test → review` for dependent tasks\n- **Parallel**: `performance-engineer + database-optimizer` for independent analysis  \n- **Validation**: `primary-agent → security-auditor` for critical components\n- **Iterative**: `review → refine → validate` for optimization tasks\n\n## 🎯 When to Use Which Agent\n\n### 🏗️ Planning \u0026 Architecture\n\n| Agent | Best For | Example Use Cases |\n|-------|----------|-------------------|\n| **[backend-architect](agents/development/backend-architect.md)** | API design, system architecture | RESTful APIs, microservices, database schemas |\n| **[frontend-developer](agents/development/frontend-developer.md)** | UI/UX planning, component design | React components, responsive layouts, state management |\n| **[cloud-architect](agents/infrastructure/cloud-architect.md)** | Infrastructure design, scalability | AWS/Azure/GCP architecture, cost optimization |\n| **[graphql-architect](agents/data-ai/graphql-architect.md)** | GraphQL system design | Schema design, resolvers, federation |\n\n### 💻 Implementation \u0026 Development  \n\n| Agent | Best For | Example Use Cases |\n|-------|----------|-------------------|\n| **[python-pro](agents/development/python-pro.md)** | Python development | Django/FastAPI apps, data processing, async programming |\n| **[golang-pro](agents/development/golang-pro.md)** | Go development | Microservices, concurrent systems, CLI tools |\n| **[typescript-pro](agents/development/typescript-pro.md)** | TypeScript development | Type-safe applications, advanced TS features |\n| **[react-pro](agents/development/react-pro.md)** | React expertise | Hooks, performance optimization, advanced patterns |\n| **[nextjs-pro](agents/development/nextjs-pro.md)** | Next.js applications | SSR/SSG, full-stack React, routing |\n\n### ☁️ Operations \u0026 Maintenance\n\n| Agent | Best For | Example Use Cases |\n|-------|----------|-------------------|\n| **[devops-incident-responder](agents/infrastructure/devops-incident-responder.md)** | Production issues, deployments | Log analysis, deployment failures, system debugging |\n| **[incident-responder](agents/infrastructure/incident-responder.md)** | Critical outages | Immediate response, crisis management, escalation |\n| **[deployment-engineer](agents/infrastructure/deployment-engineer.md)** | CI/CD, containerization | Docker, Kubernetes, pipeline configuration |\n| **[database-optimizer](agents/data-ai/database-optimizer.md)** | Database performance | Query optimization, indexing, migration strategies |\n\n### 📊 Analysis \u0026 Optimization\n\n| Agent | Best For | Example Use Cases |\n|-------|----------|-------------------|\n| **[performance-engineer](agents/infrastructure/performance-engineer.md)** | Application performance | Bottleneck analysis, caching strategies, optimization |\n| **[security-auditor](agents/security/security-auditor.md)** | Security assessment | Vulnerability scanning, OWASP compliance, threat modeling |\n| **[data-scientist](agents/data-ai/data-scientist.md)** | Data analysis | SQL queries, BigQuery, insights and reporting |\n| **[code-reviewer](agents/quality-testing/code-reviewer.md)** | Code quality | Best practices, maintainability, architectural review |\n\n### 🧪 Quality Assurance\n\n| Agent | Best For | Example Use Cases |\n|-------|----------|-------------------|\n| **[test-automator](agents/quality-testing/test-automator.md)** | Testing strategy | Unit tests, integration tests, E2E test suites |\n| **[debugger](agents/quality-testing/debugger.md)** | Bug investigation | Error analysis, test failures, troubleshooting |\n| **[architect-reviewer](agents/quality-testing/architect-review.md)** | Design validation | Architectural consistency, pattern compliance |\n\n## 📚 Best Practices\n\n- **Trust Auto-Delegation**: Claude Code excels at context analysis and optimal agent selection\n- **Provide Rich Context**: Include tech stack, constraints, and project background\n- **Use Explicit Control**: Override automatic selection when you need specific expertise\n- **Establish Quality Gates**: Build review and validation into standard workflows\n- **Match Task Complexity**: Don't over-engineer simple tasks or under-resource complex ones\n\n## 🤝 Contributing\n\n### Adding New Agents\n\nTo contribute a new subagent to the collection:\n\n1. **Follow Naming Convention**\n   - Use lowercase, hyphen-separated names (e.g., `backend-architect.md`)\n   - Name should clearly indicate the agent's domain and role\n\n2. **Use Standard Format**\n   - Include proper frontmatter with `name`, `description`, and optional `tools`\n   - Follow the structured format outlined in the [Subagent Format](#-subagent-format) section\n\n3. **Write Clear Descriptions**\n   - Description should clearly indicate when the agent should be automatically invoked\n   - Include specific keywords and contexts that trigger the agent\n\n4. **Define Specialized Behavior**\n   - Include detailed system prompt with role, expertise, and capabilities\n   - Define interaction patterns with other agents\n   - Specify decision-making frameworks and priorities\n\n5. **Test Integration**\n   - Verify the agent can be automatically invoked based on description\n   - Test explicit invocation with clear requests\n   - Ensure compatibility with existing agent coordination patterns\n\n### Quality Standards\n\n- **Domain Expertise**: Agents should demonstrate deep knowledge in their specialization\n- **Clear Boundaries**: Define what the agent does and doesn't handle\n- **Integration Ready**: Design for seamless coordination with other agents\n- **Consistent Voice**: Maintain professional, helpful, and expert tone\n\n### Submission Process\n\n1. Create the agent file following all standards\n2. Test the agent with various invocation patterns\n3. Submit a pull request with example use cases\n4. Include documentation of the agent's unique value and integration patterns\n\n## 🛠️ Troubleshooting\n\n**Common Issues:**\n\n- **Agent not selected**: Use domain-specific keywords or explicit invocation\n- **Unexpected selection**: Provide more context about tech stack and requirements\n- **Generic responses**: Request specific depth and include detailed constraints\n- **Conflicting advice**: Request reconciliation between different specialists\n\n**Resources:**\n\n- [Claude Code Documentation](https://docs.anthropic.com/en/docs/claude-code) - Official guide\n- [Subagents Documentation](https://docs.anthropic.com/en/docs/claude-code/sub-agents) - Agent system reference\n\n## 📊 Quick Reference\n\n### Most Commonly Used Agents\n\n1. **[code-reviewer](agents/quality-testing/code-reviewer.md)** - Quality assurance and best practices\n2. **[backend-architect](dagents/evelopment/backend-architect.md)** - API and system design\n3. **[frontend-developer](agents/development/frontend-developer.md)** - UI/UX implementation\n4. **[security-auditor](agents/security/security-auditor.md)** - Security validation and compliance\n5. **[performance-engineer](agents/infrastructure/performance-engineer.md)** - Optimization and bottleneck analysis\n\n### Essential Coordination Patterns\n\n- **Development**: `architect → implement → test → review`\n- **Debugging**: `debugger → specialist → validator`\n- **Optimization**: `performance-engineer + database-optimizer → validation`\n- **Security**: `primary-agent → security-auditor → approval`\n\n### Key Success Factors\n\n- ✅ Trust automatic delegation for optimal results\n- ✅ Provide rich context and specific requirements\n- ✅ Use explicit invocation strategically\n- ✅ Establish quality gates and validation patterns\n- ✅ Learn from agent coordination patterns\n\n## 🎬 Examples\n\nThese examples demonstrate real-world multi-agent coordination scenarios with detailed resource metrics to help you understand the token usage, execution time, and expected deliverables for different project complexities:\n\n- **Example 1**: Simple feature implementation (~300K tokens, ~17 minutes) - Shows efficient 4-agent coordination for focused component development\n- **Example 2**: Complex system implementation (~850K tokens, ~45 minutes) - Demonstrates enterprise-scale 7-agent orchestration with error recovery\n\nBoth examples include actual token counts, execution times, and deliverable quality to help you plan and budget for multi-agent workflows in your projects.\n\n### Example 1: ExportStep Component Implementation\n\n**User Request**: `/sc:implement` use agent-organizer to design and implement the ExportStep.tsx function, improve the UI/UX as well\n\n#### Agent Orchestration Flow\n\n![Agent Orchestration](_images/example-1-agent-organizer.png)\n\n**Step 1: agent-organizer Analysis** (56.7K tokens, 1m 20s)\n\n- Analyzed existing project structure and Zustand stores\n- Created comprehensive 7-task implementation plan\n- Assembled 3-agent specialist team for coordinated execution\n\n![Backend Implementation](_images/example-1-backend-architect.png)\n\n**Step 2: backend-architect Implementation** (99.1K tokens, 7m 31s)\n\n- Designed complete export store architecture with state management\n- Implemented format conversion utilities for SRT, VTT, ASS, JSON formats\n- Integrated Electron IPC for seamless file operations\n\n![Frontend Enhancement](_images/example-1-frontend-developer.png)\n\n**Step 3: frontend-developer Enhancement** (84.3K tokens, 5m 29s)\n\n- Created fully interactive ExportStep component with real event handlers\n- Implemented real-time preview generation based on subtitle data\n- Added accessibility compliance (WCAG 2.1 AA) and responsive design\n\n![Testing Strategy](_images/example-1-test-automator.png)\n\n**Step 4: test-automator Quality Assurance** (61.4K tokens, 2m 46s)\n\n- Developed comprehensive test coverage for format converters\n- Set up Jest and React Testing Library framework\n- Created accessibility and interaction testing strategies\n\n#### Implementation Results\n\n![Final Output](_images/example-1-final-output.png)\n\n**Complete Feature Delivery**:\n\n- 🏗️ **Backend**: Export store with state management, format conversion utilities, Electron IPC integration\n- 🎨 **Frontend**: Interactive UI with real-time preview, accessibility compliance, keyboard navigation\n- ✅ **Testing**: Comprehensive test coverage with framework setup and validation\n\n![Live Demo](_images/example-1-caption-convertion-demo.gif)\n\n#### Project Metrics\n\n**Resource Usage**:\n\n- **Total Tokens**: ~301K tokens (agent-organizer: 56K, backend-architect: 99K, frontend-developer: 84K, test-automator: 61K)\n- **Total Time**: ~30 minutes execution time\n- **Team Size**: 4 agents (1 orchestrator + 3 specialists)\n- **Files Created/Modified**: 4 major files (stores, components, utilities, tests)\n\n**Efficiency Highlights**:\n\n- **Sequential Coordination**: Each agent built upon previous work seamlessly\n- **Quality Integration**: Production-ready export system with comprehensive functionality\n- **Zero Breaking Changes**: Enhanced existing architecture without disruption\n\n### Example 2: Complex Workspace Management System\n\n**User Request**: `/sc:design` implement complex workspace management with user config persistence, multiple workspaces, workspace groups, Discord-like UI with drag-and-drop functionality\n\n#### Phase 1: Comprehensive Design \u0026 Multi-Agent Assessment\n\n![Agent Organizer Design Phase](_images/example-2-agent-organizer.png)\n\n**5-Agent Team Assembly**: backend-architect, frontend-developer, electron-pro, ux-designer, test-automator\n\n**Design Deliverables**:\n\n- Complete TypeScript interfaces for Workspace, WorkspaceGroup, and configurations\n- IndexedDB storage strategy with migration from localStorage  \n- Discord-inspired UI specifications with drag-and-drop functionality\n- Auto-save mechanisms with conflict resolution and backup strategy\n- 5-phase implementation plan with quality gates\n\n![Phase 1 Working](_images/example-2-pharse-1-working.png)\n\n**Phase 1 Assessment Results**:\n\n![Phase 1 Complete](_images/example-2-pharse-1-complete.png)\n![Phase 1 Summary](_images/example-2-pharse-1-complete-summary.png)\n\n**Comprehensive Team Assessment** (5 agents, ~400K tokens total):\n\n- 🏗️ **Backend Architecture**: IndexedDB schema, \u003c200ms startup, migration framework, auto-save strategy\n- 🎨 **Frontend Components**: Discord-inspired design, Material-UI integration, progressive enhancement\n- ⚡ **Electron Integration**: IPC architecture, security model, performance optimization\n- 🎭 **UX Design**: A+ UX Score (92/100), zero disruption, user journey validation  \n- ✅ **Testing Strategy**: 99.5% migration success, 4-layer testing pyramid, quality gates\n\n#### Complete Implementation Results\n\n![All Phases Complete](_images/example-2-all-pharse-complete.png)\n\n**Full 5-Phase Implementation**:\n\n- **Phase 1**: Assessment \u0026 Current State Analysis ✅\n- **Phase 2**: Architecture Finalization \u0026 Infrastructure ✅  \n- **Phase 3**: Core Implementation ✅\n- **Phase 4**: Integration \u0026 Migration ✅\n- **Phase 5**: Quality Assurance \u0026 Finalization ✅\n\n**Final Deliverables**:\n\n- Complete workspace management system with IndexedDB persistence\n- Discord-inspired UI with drag-and-drop workspace organization\n- Multi-workspace support with workspace groups\n- Seamless migration from existing localStorage system\n- Comprehensive test coverage and error recovery mechanisms\n\n#### Resource Metrics \u0026 Performance\n\n**Total Project Metrics**:\n\n- **Tokens Used**: ~900K tokens across all phases and error resolution\n- **Time Spent**: ~120 minutes total execution time\n- **Agents Involved**: 7 specialized agents (5 primary + 2 error resolution)\n- **Lines of Code**: ~2,400 lines across 15+ files\n- **Test Coverage**: 99.5% with comprehensive edge case handling (Should be hallucination)\n\n#### Build Error Resolution with Nested Agent Coordination\n\n![Build Error Detection](_images/example-2-build-error.png)\n\n**Second User Prompt**: `@agent-code-reviewer-pro` the application have build error please find all the build errors and ask the related sub agent to fix it. `@agent-agent-organizer`\n\n![Nested Sub-Agent Coordination](_images/example-2-nested-sub-agents.png)\n\n**Error Resolution Flow**:\n\n1. **code-reviewer-pro** (68.5K tokens, 5m 26s): Identified critical TypeScript syntax errors\n2. **agent-organizer** coordination: Systematic build error fixes with **typescript-pro**\n3. **Nested delegation**: Specialized agents called within agent workflows for targeted fixes\n\n**Error Resolution Efficiency**:\n\n- **Detection**: ~5m with code-reviewer-pro\n- **Coordination**: Instant agent-organizer response\n- **Fix Implementation**: ~30m minutes with nested typescript-pro agent\n- **Build Success**: Zero remaining errors after systematic fixes\n- **Challenging Runtime ERROR** Runtime error occur and it require manuel debugging and instruction\n\n### Key Multi-Agent Benefits\n\n- **🧠 Intelligent Orchestration**: agent-organizer coordinated 5+ agents across complex 5-phase implementation\n- **🔧 Nested Agent Support**: Error resolution through coordinated sub-agent delegation within workflows  \n- **📊 Enterprise-Scale Quality**: 850K tokens of comprehensive analysis, design, and implementation\n- **⚡ Rapid Error Recovery**: Build errors resolved in \u003c8 minutes through specialized agent coordination\n- **🎯 Domain Expertise**: Each agent contributed specialized knowledge (storage architecture, UX design, TypeScript fixes)\n\n---\n\n*Happy coding with your AI specialist team! 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