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Zhongwei Li
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model: claude-opus-4-1
---
Build data-driven features with integrated pipelines and ML capabilities using specialized agents:
[Extended thinking: This workflow orchestrates data scientists, data engineers, backend architects, and AI engineers to build features that leverage data pipelines, analytics, and machine learning. Each agent contributes their expertise to create a complete data-driven solution.]
## Phase 1: Data Analysis and Design
### 1. Data Requirements Analysis
- Use Task tool with subagent_type="data-scientist"
- Prompt: "Analyze data requirements for: $ARGUMENTS. Identify data sources, required transformations, analytics needs, and potential ML opportunities."
- Output: Data analysis report, feature engineering requirements, ML feasibility
### 2. Data Pipeline Architecture
- Use Task tool with subagent_type="data-engineer"
- Prompt: "Design data pipeline architecture for: $ARGUMENTS. Include ETL/ELT processes, data storage, streaming requirements, and integration with existing systems based on data scientist's analysis."
- Output: Pipeline architecture, technology stack, data flow diagrams
## Phase 2: Backend Integration
### 3. API and Service Design
- Use Task tool with subagent_type="backend-architect"
- Prompt: "Design backend services to support data-driven feature: $ARGUMENTS. Include APIs for data ingestion, analytics endpoints, and ML model serving based on pipeline architecture."
- Output: Service architecture, API contracts, integration patterns
### 4. Database and Storage Design
- Use Task tool with subagent_type="database-optimizer"
- Prompt: "Design optimal database schema and storage strategy for: $ARGUMENTS. Consider both transactional and analytical workloads, time-series data, and ML feature stores."
- Output: Database schemas, indexing strategies, storage recommendations
## Phase 3: ML and AI Implementation
### 5. ML Pipeline Development
- Use Task tool with subagent_type="ml-engineer"
- Prompt: "Implement ML pipeline for: $ARGUMENTS. Include feature engineering, model training, validation, and deployment based on data scientist's requirements."
- Output: ML pipeline code, model artifacts, deployment strategy
### 6. AI Integration
- Use Task tool with subagent_type="ai-engineer"
- Prompt: "Build AI-powered features for: $ARGUMENTS. Integrate LLMs, implement RAG if needed, and create intelligent automation based on ML engineer's models."
- Output: AI integration code, prompt engineering, RAG implementation
## Phase 4: Implementation and Optimization
### 7. Data Pipeline Implementation
- Use Task tool with subagent_type="data-engineer"
- Prompt: "Implement production data pipelines for: $ARGUMENTS. Include real-time streaming, batch processing, and data quality monitoring based on all previous designs."
- Output: Pipeline implementation, monitoring setup, data quality checks
### 8. Performance Optimization
- Use Task tool with subagent_type="performance-engineer"
- Prompt: "Optimize data processing and model serving performance for: $ARGUMENTS. Focus on query optimization, caching strategies, and model inference speed."
- Output: Performance improvements, caching layers, optimization report
## Phase 5: Testing and Deployment
### 9. Comprehensive Testing
- Use Task tool with subagent_type="test-automator"
- Prompt: "Create test suites for data pipelines and ML components: $ARGUMENTS. Include data validation tests, model performance tests, and integration tests."
- Output: Test suites, data quality tests, ML monitoring tests
### 10. Production Deployment
- Use Task tool with subagent_type="deployment-engineer"
- Prompt: "Deploy data-driven feature to production: $ARGUMENTS. Include pipeline orchestration, model deployment, monitoring, and rollback strategies."
- Output: Deployment configurations, monitoring dashboards, operational runbooks
## Coordination Notes
- Data flow and requirements cascade from data scientists to engineers
- ML models must integrate seamlessly with backend services
- Performance considerations apply to both data processing and model serving
- Maintain data lineage and versioning throughout the pipeline
Data-driven feature to build: $ARGUMENTS

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---
model: claude-opus-4-1
allowed-tools: Task, Read, Write, Bash(*), Glob, Grep
argument-hint: <feature-description> [--complexity=<level>] [--learning-focus=<aspect>] [--collaboration=<mode>]
description: Intelligent feature development with multi-expert orchestration and adaptive learning
---
# Intelligent Feature Development Engine
Implement complete features through multi-expert collaboration with adaptive learning, structured dissent, and cognitive harmonics optimization. Transform feature development into a comprehensive learning and building experience that delivers both functionality and team capability growth.
[Extended thinking: Enhanced workflow integrates Split Team Framework for comprehensive feature analysis, Teacher Framework for skill development during implementation, and structured dissent for robust architectural decisions. Each phase includes meta-cognitive reflection and knowledge transfer opportunities.]
## Intelligent Development Framework
### Multi-Expert Team Assembly
**Core Development Specialists:**
- **Feature Architect**: Overall design strategy and system integration
- **Frontend Specialist**: User interface and experience implementation
- **Backend Engineer**: Service logic and data management
- **Quality Assurance**: Testing strategy and validation
- **Performance Optimizer**: Efficiency and scalability considerations
- **Security Analyst**: Protection and compliance requirements
**Learning and Growth Roles:**
- **Adaptive Mentor**: Skill development and knowledge transfer
- **Pattern Recognition**: Best practice identification and application
- **Knowledge Bridge**: Cross-domain learning and connection building
**Challenge and Innovation:**
- **Constructive Critic**: Design assumption challenging and alternative generation
- **Future-Proofing Visionary**: Long-term evolution and maintainability advocacy
### Development Approach Selection
#### Option A: Collaborative Multi-Expert Development
- Use `/orchestrate` command for comprehensive team coordination
- Integrate multiple perspectives for robust feature design
- Include structured dissent for design validation
- Emphasis on learning and capability building
#### Option B: Enhanced TDD-Driven Development
- Use `/tdd-cycle` workflow with multi-expert enhancement
- Integrate constructive challenge in test design
- Include adaptive learning for TDD skill development
- Meta-cognitive reflection on testing effectiveness
#### Option C: Learning-Focused Development
- Use `/teach_concept` for skill building during implementation
- Use `/adaptive_mentor` for personalized development guidance
- Include `/pattern_discovery` for reusable pattern identification
- Emphasis on transferable knowledge and capability growth
### Adaptive Complexity Management
- **Simple Features**: Direct implementation with basic orchestration
- **Moderate Features**: Multi-expert collaboration with structured phases
- **Complex Features**: Comprehensive orchestration with structured dissent
- **Learning Features**: High educational focus with mentoring integration
## Traditional Development Steps
1. **Backend Architecture Design**
- Use Task tool with subagent_type="backend-architect"
- Prompt: "Design RESTful API and data model for: $ARGUMENTS. Include endpoint definitions, database schema, and service boundaries."
- Save the API design and schema for next agents
2. **Frontend Implementation**
- Use Task tool with subagent_type="frontend-developer"
- Prompt: "Create UI components for: $ARGUMENTS. Use the API design from backend-architect: [include API endpoints and data models from step 1]"
- Ensure UI matches the backend API contract
3. **Test Coverage**
- Use Task tool with subagent_type="test-automator"
- Prompt: "Write comprehensive tests for: $ARGUMENTS. Cover both backend API endpoints: [from step 1] and frontend components: [from step 2]"
- Include unit, integration, and e2e tests
4. **Production Deployment**
- Use Task tool with subagent_type="deployment-engineer"
- Prompt: "Prepare production deployment for: $ARGUMENTS. Include CI/CD pipeline, containerization, and monitoring for the implemented feature."
- Ensure all components from previous steps are deployment-ready
## TDD Development Steps
When using TDD mode, the sequence changes to:
1. **Test-First Backend Design**
- Use Task tool with subagent_type="tdd-orchestrator"
- Prompt: "Design and write failing tests for backend API: $ARGUMENTS. Define test cases before implementation."
- Create comprehensive test suite for API endpoints
2. **Test-First Frontend Design**
- Use Task tool with subagent_type="tdd-orchestrator"
- Prompt: "Write failing tests for frontend components: $ARGUMENTS. Include unit and integration tests."
- Define expected UI behavior through tests
3. **Incremental Implementation**
- Use Task tool with subagent_type="tdd-orchestrator"
- Prompt: "Implement features to pass tests for: $ARGUMENTS. Follow strict red-green-refactor cycles."
- Build features incrementally, guided by tests
4. **Refactoring & Optimization**
- Use Task tool with subagent_type="tdd-orchestrator"
- Prompt: "Refactor implementation while maintaining green tests: $ARGUMENTS. Optimize for maintainability."
- Improve code quality with test safety net
5. **Production Deployment**
- Use Task tool with subagent_type="deployment-engineer"
- Prompt: "Deploy TDD-developed feature: $ARGUMENTS. Verify all tests pass in CI/CD pipeline."
- Ensure test suite runs in deployment pipeline
## Execution Parameters
- **--tdd**: Enable TDD mode (uses tdd-orchestrator agent)
- **--strict-tdd**: Enforce strict red-green-refactor cycles
- **--test-coverage-min**: Set minimum test coverage threshold (default: 80%)
- **--tdd-cycle**: Use dedicated tdd-cycle workflow for granular control
Aggregate results from all agents and present a unified implementation plan.
Feature description: $ARGUMENTS

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model: claude-opus-4-1
---
Perform a comprehensive review using multiple specialized agents with explicit Task tool invocations:
[Extended thinking: This workflow performs a thorough multi-perspective review by orchestrating specialized review agents. Each agent examines different aspects and the results are consolidated into a unified action plan. Includes TDD compliance verification when enabled.]
## Review Configuration
- **Standard Review**: Traditional comprehensive review (default)
- **TDD-Enhanced Review**: Includes TDD compliance and test-first verification
- Enable with **--tdd-review** flag
- Verifies red-green-refactor cycle adherence
- Checks test-first implementation patterns
Execute parallel reviews using Task tool with specialized agents:
## 1. Code Quality Review
- Use Task tool with subagent_type="code-reviewer"
- Prompt: "Review code quality and maintainability for: $ARGUMENTS. Check for code smells, readability, documentation, and adherence to best practices."
- Focus: Clean code principles, SOLID, DRY, naming conventions
## 2. Security Audit
- Use Task tool with subagent_type="security-auditor"
- Prompt: "Perform security audit on: $ARGUMENTS. Check for vulnerabilities, OWASP compliance, authentication issues, and data protection."
- Focus: Injection risks, authentication, authorization, data encryption
## 3. Architecture Review
- Use Task tool with subagent_type="architect-reviewer"
- Prompt: "Review architectural design and patterns in: $ARGUMENTS. Evaluate scalability, maintainability, and adherence to architectural principles."
- Focus: Service boundaries, coupling, cohesion, design patterns
## 4. Performance Analysis
- Use Task tool with subagent_type="performance-engineer"
- Prompt: "Analyze performance characteristics of: $ARGUMENTS. Identify bottlenecks, resource usage, and optimization opportunities."
- Focus: Response times, memory usage, database queries, caching
## 5. Test Coverage Assessment
- Use Task tool with subagent_type="test-automator"
- Prompt: "Evaluate test coverage and quality for: $ARGUMENTS. Assess unit tests, integration tests, and identify gaps in test coverage."
- Focus: Coverage metrics, test quality, edge cases, test maintainability
## 6. TDD Compliance Review (When --tdd-review is enabled)
- Use Task tool with subagent_type="tdd-orchestrator"
- Prompt: "Verify TDD compliance for: $ARGUMENTS. Check for test-first development patterns, red-green-refactor cycles, and test-driven design."
- Focus on TDD metrics:
- **Test-First Verification**: Were tests written before implementation?
- **Red-Green-Refactor Cycles**: Evidence of proper TDD cycles
- **Test Coverage Trends**: Coverage growth patterns during development
- **Test Granularity**: Appropriate test size and scope
- **Refactoring Evidence**: Code improvements with test safety net
- **Test Quality**: Tests that drive design, not just verify behavior
## Consolidated Report Structure
Compile all feedback into a unified report:
- **Critical Issues** (must fix): Security vulnerabilities, broken functionality, architectural flaws
- **Recommendations** (should fix): Performance bottlenecks, code quality issues, missing tests
- **Suggestions** (nice to have): Refactoring opportunities, documentation improvements
- **Positive Feedback** (what's done well): Good practices to maintain and replicate
### TDD-Specific Metrics (When --tdd-review is enabled)
Additional TDD compliance report section:
- **TDD Adherence Score**: Percentage of code developed using TDD methodology
- **Test-First Evidence**: Commits showing tests before implementation
- **Cycle Completeness**: Percentage of complete red-green-refactor cycles
- **Test Design Quality**: How well tests drive the design
- **Coverage Delta Analysis**: Coverage changes correlated with feature additions
- **Refactoring Frequency**: Evidence of continuous improvement
- **Test Execution Time**: Performance of test suite
- **Test Stability**: Flakiness and reliability metrics
## Review Options
- **--tdd-review**: Enable TDD compliance checking
- **--strict-tdd**: Fail review if TDD practices not followed
- **--tdd-metrics**: Generate detailed TDD metrics report
- **--test-first-only**: Only review code with test-first evidence
Target: $ARGUMENTS

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model: claude-opus-4-1
---
Implement a full-stack feature across multiple platforms with coordinated agent orchestration:
[Extended thinking: This workflow orchestrates a comprehensive feature implementation across backend, frontend, mobile, and API layers. Each agent builds upon the work of previous agents to create a cohesive multi-platform solution.]
## Phase 1: Architecture and API Design
### 1. Backend Architecture
- Use Task tool with subagent_type="backend-architect"
- Prompt: "Design backend architecture for: $ARGUMENTS. Include service boundaries, data models, and technology recommendations."
- Output: Service architecture, database schema, API structure
### 2. GraphQL API Design (if applicable)
- Use Task tool with subagent_type="graphql-architect"
- Prompt: "Design GraphQL schema and resolvers for: $ARGUMENTS. Build on the backend architecture from previous step. Include types, queries, mutations, and subscriptions."
- Output: GraphQL schema, resolver structure, federation strategy
## Phase 2: Implementation
### 3. Frontend Development
- Use Task tool with subagent_type="frontend-developer"
- Prompt: "Implement web frontend for: $ARGUMENTS. Use the API design from previous steps. Include responsive UI, state management, and API integration."
- Output: React/Vue/Angular components, state management, API client
### 4. Mobile Development
- Use Task tool with subagent_type="mobile-developer"
- Prompt: "Implement mobile app features for: $ARGUMENTS. Ensure consistency with web frontend and use the same API. Include offline support and native integrations."
- Output: React Native/Flutter implementation, offline sync, push notifications
## Phase 3: Quality Assurance
### 5. Comprehensive Testing
- Use Task tool with subagent_type="test-automator"
- Prompt: "Create test suites for: $ARGUMENTS. Cover backend APIs, frontend components, mobile app features, and integration tests across all platforms."
- Output: Unit tests, integration tests, e2e tests, test documentation
### 6. Security Review
- Use Task tool with subagent_type="security-auditor"
- Prompt: "Audit security across all implementations for: $ARGUMENTS. Check API security, frontend vulnerabilities, and mobile app security."
- Output: Security report, remediation steps
## Phase 4: Optimization and Deployment
### 7. Performance Optimization
- Use Task tool with subagent_type="performance-engineer"
- Prompt: "Optimize performance across all platforms for: $ARGUMENTS. Focus on API response times, frontend bundle size, and mobile app performance."
- Output: Performance improvements, caching strategies, optimization report
### 8. Deployment Preparation
- Use Task tool with subagent_type="deployment-engineer"
- Prompt: "Prepare deployment for all components of: $ARGUMENTS. Include CI/CD pipelines, containerization, and monitoring setup."
- Output: Deployment configurations, monitoring setup, rollout strategy
## Coordination Notes
- Each agent receives outputs from previous agents
- Maintain consistency across all platforms
- Ensure API contracts are honored by all clients
- Document integration points between components
Feature to implement: $ARGUMENTS

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model: claude-opus-4-1
---
Complete Git workflow using specialized agents:
1. code-reviewer: Review uncommitted changes
2. test-automator: Ensure tests pass
3. deployment-engineer: Verify deployment readiness
4. Create commit message following conventions
5. Push and create PR with proper description
Target branch: $ARGUMENTS

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model: claude-opus-4-1
---
Improve an existing agent based on recent performance:
1. Analyze recent uses of: $ARGUMENTS
2. Identify patterns in:
- Failed tasks
- User corrections
- Suboptimal outputs
3. Update the agent's prompt with:
- New examples
- Clarified instructions
- Additional constraints
4. Test on recent scenarios
5. Save improved version

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model: claude-opus-4-1
---
Respond to production incidents with coordinated agent expertise for rapid resolution:
[Extended thinking: This workflow handles production incidents with urgency and precision. Multiple specialized agents work together to identify root causes, implement fixes, and prevent recurrence.]
## Phase 1: Immediate Response
### 1. Incident Assessment
- Use Task tool with subagent_type="incident-responder"
- Prompt: "URGENT: Assess production incident: $ARGUMENTS. Determine severity, impact, and immediate mitigation steps. Time is critical."
- Output: Incident severity, impact assessment, immediate actions
### 2. Initial Troubleshooting
- Use Task tool with subagent_type="devops-troubleshooter"
- Prompt: "Investigate production issue: $ARGUMENTS. Check logs, metrics, recent deployments, and system health. Identify potential root causes."
- Output: Initial findings, suspicious patterns, potential causes
## Phase 2: Root Cause Analysis
### 3. Deep Debugging
- Use Task tool with subagent_type="debugger"
- Prompt: "Debug production issue: $ARGUMENTS using findings from initial investigation. Analyze stack traces, reproduce issue if possible, identify exact root cause."
- Output: Root cause identification, reproduction steps, debug analysis
### 4. Performance Analysis (if applicable)
- Use Task tool with subagent_type="performance-engineer"
- Prompt: "Analyze performance aspects of incident: $ARGUMENTS. Check for resource exhaustion, bottlenecks, or performance degradation."
- Output: Performance metrics, resource analysis, bottleneck identification
### 5. Database Investigation (if applicable)
- Use Task tool with subagent_type="database-optimizer"
- Prompt: "Investigate database-related aspects of incident: $ARGUMENTS. Check for locks, slow queries, connection issues, or data corruption."
- Output: Database health report, query analysis, data integrity check
## Phase 3: Resolution Implementation
### 6. Fix Development
- Use Task tool with subagent_type="backend-architect"
- Prompt: "Design and implement fix for incident: $ARGUMENTS based on root cause analysis. Ensure fix is safe for immediate production deployment."
- Output: Fix implementation, safety analysis, rollout strategy
### 7. Emergency Deployment
- Use Task tool with subagent_type="deployment-engineer"
- Prompt: "Deploy emergency fix for incident: $ARGUMENTS. Implement with minimal risk, include rollback plan, and monitor deployment closely."
- Output: Deployment execution, rollback procedures, monitoring setup
## Phase 4: Stabilization and Prevention
### 8. System Stabilization
- Use Task tool with subagent_type="devops-troubleshooter"
- Prompt: "Stabilize system after incident fix: $ARGUMENTS. Monitor system health, clear any backlogs, and ensure full recovery."
- Output: System health report, recovery metrics, stability confirmation
### 9. Security Review (if applicable)
- Use Task tool with subagent_type="security-auditor"
- Prompt: "Review security implications of incident: $ARGUMENTS. Check for any security breaches, data exposure, or vulnerabilities exploited."
- Output: Security assessment, breach analysis, hardening recommendations
## Phase 5: Post-Incident Activities
### 10. Monitoring Enhancement
- Use Task tool with subagent_type="devops-troubleshooter"
- Prompt: "Enhance monitoring to prevent recurrence of: $ARGUMENTS. Add alerts, improve observability, and set up early warning systems."
- Output: New monitoring rules, alert configurations, observability improvements
### 11. Test Coverage
- Use Task tool with subagent_type="test-automator"
- Prompt: "Create tests to prevent regression of incident: $ARGUMENTS. Include unit tests, integration tests, and chaos engineering scenarios."
- Output: Test implementations, regression prevention, chaos tests
### 12. Documentation
- Use Task tool with subagent_type="incident-responder"
- Prompt: "Document incident postmortem for: $ARGUMENTS. Include timeline, root cause, impact, resolution, and lessons learned. No blame, focus on improvement."
- Output: Postmortem document, action items, process improvements
## Coordination Notes
- Speed is critical in early phases - parallel agent execution where possible
- Communication between agents must be clear and rapid
- All changes must be safe and reversible
- Document everything for postmortem analysis
Production incident: $ARGUMENTS

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model: claude-opus-4-1
---
Modernize legacy code using expert agents:
1. legacy-modernizer: Analyze and plan modernization
2. test-automator: Create tests for legacy code
3. code-reviewer: Review modernization plan
4. python-pro/golang-pro: Implement modernization
5. security-auditor: Verify security improvements
6. performance-engineer: Validate performance
Target: $ARGUMENTS

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model: claude-opus-4-1
---
# Machine Learning Pipeline
Design and implement a complete ML pipeline for: $ARGUMENTS
Create a production-ready pipeline including:
1. **Data Ingestion**:
- Multiple data source connectors
- Schema validation with Pydantic
- Data versioning strategy
- Incremental loading capabilities
2. **Feature Engineering**:
- Feature transformation pipeline
- Feature store integration
- Statistical validation
- Handling missing data and outliers
3. **Model Training**:
- Experiment tracking (MLflow/W&B)
- Hyperparameter optimization
- Cross-validation strategy
- Model versioning
4. **Model Evaluation**:
- Comprehensive metrics
- A/B testing framework
- Bias detection
- Performance monitoring
5. **Deployment**:
- Model serving API
- Batch/stream prediction
- Model registry
- Rollback capabilities
6. **Monitoring**:
- Data drift detection
- Model performance tracking
- Alert system
- Retraining triggers
Include error handling, logging, and make it cloud-agnostic. Use modern tools like DVC, MLflow, or similar. Ensure reproducibility and scalability.

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model: claude-opus-4-1
---
Build the same feature across multiple platforms:
Run in parallel:
- frontend-developer: Web implementation
- mobile-developer: Mobile app implementation
- api-documenter: API documentation
Ensure consistency across all platforms.
Feature specification: $ARGUMENTS

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model: claude-opus-4-1
---
Optimize application performance end-to-end using specialized performance and optimization agents:
[Extended thinking: This workflow coordinates multiple agents to identify and fix performance bottlenecks across the entire stack. From database queries to frontend rendering, each agent contributes their expertise to create a highly optimized application.]
## Phase 1: Performance Analysis
### 1. Application Profiling
- Use Task tool with subagent_type="performance-engineer"
- Prompt: "Profile application performance for: $ARGUMENTS. Identify CPU, memory, and I/O bottlenecks. Include flame graphs, memory profiles, and resource utilization metrics."
- Output: Performance profile, bottleneck analysis, optimization priorities
### 2. Database Performance Analysis
- Use Task tool with subagent_type="database-optimizer"
- Prompt: "Analyze database performance for: $ARGUMENTS. Review query execution plans, identify slow queries, check indexing, and analyze connection pooling."
- Output: Query optimization report, index recommendations, schema improvements
## Phase 2: Backend Optimization
### 3. Backend Code Optimization
- Use Task tool with subagent_type="performance-engineer"
- Prompt: "Optimize backend code for: $ARGUMENTS based on profiling results. Focus on algorithm efficiency, caching strategies, and async operations."
- Output: Optimized code, caching implementation, performance improvements
### 4. API Optimization
- Use Task tool with subagent_type="backend-architect"
- Prompt: "Optimize API design and implementation for: $ARGUMENTS. Consider pagination, response compression, field filtering, and batch operations."
- Output: Optimized API endpoints, GraphQL query optimization, response time improvements
## Phase 3: Frontend Optimization
### 5. Frontend Performance
- Use Task tool with subagent_type="frontend-developer"
- Prompt: "Optimize frontend performance for: $ARGUMENTS. Focus on bundle size, lazy loading, code splitting, and rendering performance. Implement Core Web Vitals improvements."
- Output: Optimized bundles, lazy loading implementation, performance metrics
### 6. Mobile App Optimization
- Use Task tool with subagent_type="mobile-developer"
- Prompt: "Optimize mobile app performance for: $ARGUMENTS. Focus on startup time, memory usage, battery efficiency, and offline performance."
- Output: Optimized mobile code, reduced app size, improved battery life
## Phase 4: Infrastructure Optimization
### 7. Cloud Infrastructure Optimization
- Use Task tool with subagent_type="cloud-architect"
- Prompt: "Optimize cloud infrastructure for: $ARGUMENTS. Review auto-scaling, instance types, CDN usage, and geographic distribution."
- Output: Infrastructure improvements, cost optimization, scaling strategy
### 8. Deployment Optimization
- Use Task tool with subagent_type="deployment-engineer"
- Prompt: "Optimize deployment and build processes for: $ARGUMENTS. Improve CI/CD performance, implement caching, and optimize container images."
- Output: Faster builds, optimized containers, improved deployment times
## Phase 5: Monitoring and Validation
### 9. Performance Monitoring Setup
- Use Task tool with subagent_type="devops-troubleshooter"
- Prompt: "Set up comprehensive performance monitoring for: $ARGUMENTS. Include APM, real user monitoring, and custom performance metrics."
- Output: Monitoring dashboards, alert thresholds, SLO definitions
### 10. Performance Testing
- Use Task tool with subagent_type="test-automator"
- Prompt: "Create performance test suites for: $ARGUMENTS. Include load tests, stress tests, and performance regression tests."
- Output: Performance test suite, benchmark results, regression prevention
## Coordination Notes
- Performance metrics guide optimization priorities
- Each optimization must be validated with measurements
- Consider trade-offs between different performance aspects
- Document all optimizations and their impact
Performance optimization target: $ARGUMENTS

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---
model: claude-opus-4-1
allowed-tools: Task, Read, Write, Bash(*), Glob, Grep
argument-hint: <system-or-application> [--threat-model=<category>] [--compliance=<framework>] [--learning=<security-education>]
description: Multi-expert security hardening with threat modeling and adaptive security education
---
# Advanced Security Hardening Engine
Implement comprehensive security measures through multi-expert collaboration with threat modeling, structured dissent, and adaptive security learning. Transform security implementation into a sophisticated, educational process that builds both robust protection and security expertise.
[Extended thinking: Enhanced workflow integrates multi-perspective threat analysis, constructive challenge of security assumptions, adaptive learning for security skill development, and structured dissent to identify security blind spots and strengthen defenses.]
## Phase 1: Multi-Expert Threat Analysis and Security Assessment
### 1. Comprehensive Security Multi-Perspective Analysis
[Extended thinking: Leverage multiple expert perspectives to ensure comprehensive threat identification and risk assessment from different attack vectors and defense viewpoints.]
**Multi-Expert Threat Assessment:**
- Use `/multi_perspective` command with `"$ARGUMENTS security analysis" security --perspectives=6 --integration=comprehensive --depth=systematic`
- **Security Architect**: Overall security design and defense-in-depth strategy
- **Penetration Tester**: Offensive perspective identifying attack vectors and vulnerabilities
- **Compliance Specialist**: Regulatory requirements and audit preparation
- **Infrastructure Security**: Network, server, and deployment security concerns
- **Application Security**: Code-level vulnerabilities and secure development practices
- **Incident Responder**: Monitoring, detection, and response capability assessment
**Threat Model Challenge:**
- Use `/constructive_dissent` command with `"Primary security threats for $ARGUMENTS" --dissent-intensity=rigorous --alternatives=3 --focus=threat-assumptions`
- Challenge assumptions about primary threats and attack vectors
- Generate alternative threat scenarios and attack pathways
- Question whether security focus areas are appropriately prioritized
**Security Learning Integration:**
- Use `/teach_concept` command with `"threat modeling for $ARGUMENTS" intermediate --approach=experiential --pathway=analytical`
- Build understanding of security principles through hands-on threat analysis
- Develop security intuition and pattern recognition skills
- Create transferable security knowledge for future projects
### 2. Enhanced Architecture Security Design
[Extended thinking: Create robust security architecture through collaborative design with red-team thinking and structured challenge of security assumptions.]
**Collaborative Security Architecture:**
- Use `/orchestrate` command with `"design secure architecture for $ARGUMENTS" complex security-auditor,backend-architect,network-engineer,devops-troubleshooter --mode=dialectical`
- Generate secure architecture through multi-expert collaboration
- Include threat modeling, defense layers, and security boundaries
- Ensure architecture supports zero-trust principles and defense-in-depth
**Red Team Architecture Challenge:**
- Use `/guest_expert` command with `"cybersecurity" "How would you attack this $ARGUMENTS architecture?" --expertise-depth=authority --perspective-count=3 --style=adversarial`
- Assume attacker perspective to identify architecture weaknesses
- Generate attack scenarios and exploitation pathways
- Validate architecture against sophisticated threat actors
**Security Assumption Audit:**
- Use `/assumption_audit` command with `"Security architecture assumptions for $ARGUMENTS" --audit-depth=paradigmatic --challenge-method=red-team-analysis`
- Challenge fundamental assumptions about security boundaries and trust models
- Examine assumptions about user behavior, system reliability, and threat environment
- Generate alternative security paradigms and approaches
## Phase 2: Security Implementation
### 3. Backend Security Hardening
- Use Task tool with subagent_type="backend-architect"
- Prompt: "Implement backend security measures for: $ARGUMENTS. Include authentication, authorization, input validation, and secure data handling based on security audit findings."
- Output: Secure API implementations, auth middleware, validation layers
### 4. Infrastructure Security
- Use Task tool with subagent_type="devops-troubleshooter"
- Prompt: "Implement infrastructure security for: $ARGUMENTS. Configure firewalls, secure secrets management, implement least privilege access, and set up security monitoring."
- Output: Infrastructure security configs, secrets management, monitoring setup
### 5. Frontend Security
- Use Task tool with subagent_type="frontend-developer"
- Prompt: "Implement frontend security measures for: $ARGUMENTS. Include CSP headers, XSS prevention, secure authentication flows, and sensitive data handling."
- Output: Secure frontend code, CSP policies, auth integration
## Phase 3: Compliance and Testing
### 6. Compliance Verification
- Use Task tool with subagent_type="security-auditor"
- Prompt: "Verify compliance with security standards for: $ARGUMENTS. Check OWASP Top 10, GDPR, SOC2, or other relevant standards. Validate all security implementations."
- Output: Compliance report, remediation requirements
### 7. Security Testing
- Use Task tool with subagent_type="test-automator"
- Prompt: "Create security test suites for: $ARGUMENTS. Include penetration tests, security regression tests, and automated vulnerability scanning."
- Output: Security test suite, penetration test results, CI/CD integration
## Phase 4: Deployment and Monitoring
### 8. Secure Deployment
- Use Task tool with subagent_type="deployment-engineer"
- Prompt: "Implement secure deployment pipeline for: $ARGUMENTS. Include security gates, vulnerability scanning in CI/CD, and secure configuration management."
- Output: Secure CI/CD pipeline, deployment security checks, rollback procedures
### 9. Security Monitoring Setup
- Use Task tool with subagent_type="devops-troubleshooter"
- Prompt: "Set up security monitoring and incident response for: $ARGUMENTS. Include intrusion detection, log analysis, and automated alerting."
- Output: Security monitoring dashboards, alert rules, incident response procedures
## Coordination Notes
- Security findings from each phase inform subsequent implementations
- All agents must prioritize security in their recommendations
- Regular security reviews between phases ensure nothing is missed
- Document all security decisions and trade-offs
Security hardening target: $ARGUMENTS

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---
model: claude-opus-4-1
---
Intelligently fix the issue using automatic agent selection with explicit Task tool invocations:
[Extended thinking: This workflow analyzes the issue and automatically routes to the most appropriate specialist agent(s). Complex issues may require multiple agents working together.]
First, analyze the issue to categorize it, then use Task tool with the appropriate agent:
## Analysis Phase
Examine the issue: "$ARGUMENTS" to determine the problem domain.
## Agent Selection and Execution
### For Deployment/Infrastructure Issues
If the issue involves deployment failures, infrastructure problems, or DevOps concerns:
- Use Task tool with subagent_type="devops-troubleshooter"
- Prompt: "Debug and fix this deployment/infrastructure issue: $ARGUMENTS"
### For Code Errors and Bugs
If the issue involves application errors, exceptions, or functional bugs:
- Use Task tool with subagent_type="debugger"
- Prompt: "Analyze and fix this code error: $ARGUMENTS. Provide root cause analysis and solution."
### For Database Performance
If the issue involves slow queries, database bottlenecks, or data access patterns:
- Use Task tool with subagent_type="database-optimizer"
- Prompt: "Optimize database performance for: $ARGUMENTS. Include query analysis, indexing strategies, and schema improvements."
### For Application Performance
If the issue involves slow response times, high resource usage, or performance degradation:
- Use Task tool with subagent_type="performance-engineer"
- Prompt: "Profile and optimize application performance issue: $ARGUMENTS. Identify bottlenecks and provide optimization strategies."
### For Legacy Code Issues
If the issue involves outdated code, deprecated patterns, or technical debt:
- Use Task tool with subagent_type="legacy-modernizer"
- Prompt: "Modernize and fix legacy code issue: $ARGUMENTS. Provide migration path and updated implementation."
## Multi-Domain Coordination
For complex issues spanning multiple domains:
1. Use primary agent based on main symptom
2. Use secondary agents for related aspects
3. Coordinate fixes across all affected areas
4. Verify integration between different fixes
Issue: $ARGUMENTS

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---
model: claude-opus-4-1
allowed-tools: Task, Read, Write, Bash(*), Grep, Glob
argument-hint: <feature-requirement> [--complexity=<level>] [--learning-mode=<approach>] [--dissent-level=<intensity>]
description: Test-Driven Development with multi-expert orchestration and adaptive learning integration
---
# Advanced TDD Orchestration Engine
Execute comprehensive Test-Driven Development through multi-expert collaboration with structured dissent, adaptive learning, and cognitive harmonics optimization. Transform traditional TDD into an intelligent, self-improving development process that builds both code quality and team understanding.
[Extended thinking: This enhanced workflow integrates Split Team Framework for multi-perspective analysis, Teacher Framework for adaptive learning, and structured dissent protocols for robust test design. Each phase includes constructive challenge mechanisms and meta-cognitive reflection for continuous improvement.]
## Configuration
### Multi-Expert Team Configuration
**Core TDD Specialists:**
- **Test Strategist**: Overall test approach and architecture design
- **Quality Guardian**: Test completeness and edge case coverage advocate
- **Implementation Guide**: Code structure and maintainability focus
- **Performance Analyst**: Testing efficiency and execution speed optimization
- **Usability Advocate**: Developer experience and test readability champion
**Challenge Perspectives:**
- **Constructive Critic**: Questions test assumptions and approaches
- **Pragmatic Realist**: Balances ideal practices with practical constraints
- **Future-Proofing Visionary**: Considers long-term maintainability and evolution
### Adaptive Learning Parameters
- **Novice Mode**: Heavy scaffolding, detailed explanations, step-by-step guidance
- **Intermediate Mode**: Moderate guidance with pattern recognition development
- **Advanced Mode**: Minimal scaffolding, collaborative peer-level interaction
- **Expert Mode**: Innovation-focused with paradigm challenging
### Quality Thresholds
- **Coverage Standards**: Line coverage 80%, Branch coverage 75%, Critical path 100%
- **Complexity Limits**: Cyclomatic complexity ≤ 10, Method length ≤ 20 lines
- **Architecture Standards**: Class length ≤ 200 lines, Duplicate blocks ≤ 3 lines
- **Test Quality**: Fast (<100ms), Isolated, Repeatable, Self-validating
## Phase 1: Multi-Expert Requirements Analysis and Test Strategy
### 1. Collaborative Requirements Analysis
[Extended thinking: Leverage multi-perspective analysis to ensure comprehensive understanding of requirements from different stakeholder viewpoints, reducing blind spots and improving test coverage.]
**Primary Analysis:**
- Use `/multi_perspective` command with `"$ARGUMENTS requirements analysis" technical --perspectives=5 --integration=comprehensive`
- **Test Strategist**: Overall testing approach and comprehensive coverage strategy
- **Quality Guardian**: Edge cases, error conditions, and boundary value identification
- **Implementation Guide**: Code structure implications and testability requirements
- **Performance Analyst**: Performance testing needs and execution constraints
- **Usability Advocate**: Developer experience and test maintainability considerations
**Constructive Challenge:**
- Use `/constructive_dissent` command with `"Proposed test strategy for $ARGUMENTS" --dissent-intensity=systematic --alternatives=2`
- Challenge assumptions about what needs testing and how
- Generate alternative testing approaches for comparison
- Question whether requirements are testable as specified
**Adaptive Learning Integration:**
- Use `/teach_concept` command with `"test strategy for $ARGUMENTS" intermediate --approach=socratic` for learning-oriented sessions
- Build understanding of testing principles through guided discovery
- Develop pattern recognition for similar future testing challenges
### 2. Enhanced Test Architecture Design
[Extended thinking: Create robust test architecture through collaborative design with structured disagreement to identify potential weaknesses and improvements.]
**Collaborative Design:**
- Use `/orchestrate` command with `"design test architecture for $ARGUMENTS" moderate test-automator,performance-engineer,architect-review --mode=dialectical`
- Generate test architecture through structured collaboration
- Include fixture design, mock strategy, and test data management
- Ensure architecture supports TDD principles: fast, isolated, repeatable, self-validating
**Architecture Validation:**
- Use `/assumption_audit` command with `"Test architecture assumptions for $ARGUMENTS" --audit-depth=structural --challenge-method=alternative-generation`
- Challenge fundamental assumptions about test organization and structure
- Generate alternative architectural approaches for comparison
- Validate architecture against long-term maintainability and scalability needs
## Phase 2: RED - Write Failing Tests
### 3. Write Unit Tests (Failing)
- Use Task tool with subagent_type="test-automator"
- Prompt: "Write FAILING unit tests for: $ARGUMENTS. Tests must fail initially. Include edge cases, error scenarios, and happy paths. DO NOT implement production code."
- Output: Failing unit tests, test documentation
- **CRITICAL**: Verify all tests fail with expected error messages
### 4. Verify Test Failure
- Use Task tool with subagent_type="code-reviewer"
- Prompt: "Verify that all tests for: $ARGUMENTS are failing correctly. Ensure failures are for the right reasons (missing implementation, not test errors). Confirm no false positives."
- Output: Test failure verification report
- **GATE**: Do not proceed until all tests fail appropriately
## Phase 3: GREEN - Make Tests Pass
### 5. Minimal Implementation
- Use Task tool with subagent_type="backend-architect"
- Prompt: "Implement MINIMAL code to make tests pass for: $ARGUMENTS. Focus only on making tests green. Do not add extra features or optimizations. Keep it simple."
- Output: Minimal working implementation
- Constraint: No code beyond what's needed to pass tests
### 6. Verify Test Success
- Use Task tool with subagent_type="test-automator"
- Prompt: "Run all tests for: $ARGUMENTS and verify they pass. Check test coverage metrics. Ensure no tests were accidentally broken."
- Output: Test execution report, coverage metrics
- **GATE**: All tests must pass before proceeding
## Phase 4: REFACTOR - Improve Code Quality
### 7. Code Refactoring
- Use Task tool with subagent_type="code-reviewer"
- Prompt: "Refactor implementation for: $ARGUMENTS while keeping tests green. Apply SOLID principles, remove duplication, improve naming, and optimize performance. Run tests after each refactoring."
- Output: Refactored code, refactoring report
- Constraint: Tests must remain green throughout
### 8. Test Refactoring
- Use Task tool with subagent_type="test-automator"
- Prompt: "Refactor tests for: $ARGUMENTS. Remove test duplication, improve test names, extract common fixtures, and enhance test readability. Ensure tests still provide same coverage."
- Output: Refactored tests, improved test structure
- Validation: Coverage metrics unchanged or improved
## Phase 5: Integration and System Tests
### 9. Write Integration Tests (Failing First)
- Use Task tool with subagent_type="test-automator"
- Prompt: "Write FAILING integration tests for: $ARGUMENTS. Test component interactions, API contracts, and data flow. Tests must fail initially."
- Output: Failing integration tests
- Validation: Tests fail due to missing integration logic
### 10. Implement Integration
- Use Task tool with subagent_type="backend-architect"
- Prompt: "Implement integration code for: $ARGUMENTS to make integration tests pass. Focus on component interaction and data flow."
- Output: Integration implementation
- Validation: All integration tests pass
## Phase 6: Continuous Improvement Cycle
### 11. Performance and Edge Case Tests
- Use Task tool with subagent_type="test-automator"
- Prompt: "Add performance tests and additional edge case tests for: $ARGUMENTS. Include stress tests, boundary tests, and error recovery tests."
- Output: Extended test suite
- Metric: Increased test coverage and scenario coverage
### 12. Final Code Review
- Use Task tool with subagent_type="architect-review"
- Prompt: "Perform comprehensive review of: $ARGUMENTS. Verify TDD process was followed, check code quality, test quality, and coverage. Suggest improvements."
- Output: Review report, improvement suggestions
- Action: Implement critical suggestions while maintaining green tests
## Incremental Development Mode
For test-by-test development:
1. Write ONE failing test
2. Make ONLY that test pass
3. Refactor if needed
4. Repeat for next test
Use this approach by adding `--incremental` flag to focus on one test at a time.
## Test Suite Mode
For comprehensive test suite development:
1. Write ALL tests for a feature/module (failing)
2. Implement code to pass ALL tests
3. Refactor entire module
4. Add integration tests
Use this approach by adding `--suite` flag for batch test development.
## Validation Checkpoints
### RED Phase Validation
- [ ] All tests written before implementation
- [ ] All tests fail with meaningful error messages
- [ ] Test failures are due to missing implementation
- [ ] No test passes accidentally
### GREEN Phase Validation
- [ ] All tests pass
- [ ] No extra code beyond test requirements
- [ ] Coverage meets minimum thresholds
- [ ] No test was modified to make it pass
### REFACTOR Phase Validation
- [ ] All tests still pass after refactoring
- [ ] Code complexity reduced
- [ ] Duplication eliminated
- [ ] Performance improved or maintained
- [ ] Test readability improved
## Coverage Reports
Generate coverage reports after each phase:
- Line coverage
- Branch coverage
- Function coverage
- Statement coverage
## Failure Recovery
If TDD discipline is broken:
1. **STOP** immediately
2. Identify which phase was violated
3. Rollback to last valid state
4. Resume from correct phase
5. Document lesson learned
## TDD Metrics Tracking
Track and report:
- Time in each phase (Red/Green/Refactor)
- Number of test-implementation cycles
- Coverage progression
- Refactoring frequency
- Defect escape rate
## Anti-Patterns to Avoid
- Writing implementation before tests
- Writing tests that already pass
- Skipping the refactor phase
- Writing multiple features without tests
- Modifying tests to make them pass
- Ignoring failing tests
- Writing tests after implementation
## Success Criteria
- 100% of code written test-first
- All tests pass continuously
- Coverage exceeds thresholds
- Code complexity within limits
- Zero defects in covered code
- Clear test documentation
- Fast test execution (< 5 seconds for unit tests)
## Notes
- Enforce strict RED-GREEN-REFACTOR discipline
- Each phase must be completed before moving to next
- Tests are the specification
- If a test is hard to write, the design needs improvement
- Refactoring is NOT optional
- Keep test execution fast
- Tests should be independent and isolated
TDD implementation for: $ARGUMENTS

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