mirror of
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feat: Add Role Analysis Reviewer Agent and validation template
- Introduced Role Analysis Reviewer Agent to validate role analysis outputs against templates and quality standards. - Created a detailed validation ruleset for the system-architect role, including mandatory and recommended sections. - Added JSON validation report structure for output. - Implemented execution command for validation process. test: Add UX tests for HookCard component - Created comprehensive tests for HookCard component, focusing on delete confirmation UX pattern. - Verified confirmation dialog appearance, deletion functionality, and button interactions. - Ensured proper handling of state updates and visual feedback for enabled/disabled status. test: Add UX tests for ThemeSelector component - Developed tests for ThemeSelector component, emphasizing delete confirmation UX pattern. - Validated confirmation dialog display, deletion actions, and toast notifications for undo functionality. - Ensured proper management of theme slots and state updates. feat: Implement useDebounce hook - Added useDebounce hook to delay expensive computations or API calls, enhancing performance. feat: Create System Architect Analysis Template - Developed a comprehensive template for system architect role analysis, covering required sections such as architecture overview, data model, state machine, error handling strategy, observability requirements, configuration model, and boundary scenarios. - Included examples and templates for each section to guide users in producing SPEC.md-level precision modeling.
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catlog22
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.claude/skills/team-lifecycle-v3/roles/specialists/README.md
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.claude/skills/team-lifecycle-v3/roles/specialists/README.md
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# Role Library - Team Lifecycle v3
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Dynamic role specification library for team-lifecycle-v3. Role definitions are loaded at runtime to extend the built-in role detection table.
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## Purpose
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- Extend role inference beyond hardcoded defaults
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- Support domain-specific specialist roles
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- Enable dynamic role injection based on task keywords
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- Maintain backward compatibility with v2 core roles
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## Role Categories
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### Core Pipeline Roles (v2 inherited)
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- analyst, writer, planner, executor, tester, reviewer
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- architect, fe-developer, fe-qa
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### Specialist Roles (v3 new)
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- **orchestrator**: Complex task decomposition and parallel coordination
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- **security-expert**: Security analysis and vulnerability scanning
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- **performance-optimizer**: Performance profiling and optimization
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- **data-engineer**: Data pipeline and schema design
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- **devops-engineer**: Infrastructure as code and CI/CD
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- **ml-engineer**: Machine learning pipeline implementation
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## Dynamic Role Injection
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Specialist roles are injected at runtime when coordinator detects matching keywords in task descriptions:
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| Keywords | Injected Role |
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|----------|---------------|
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| security, vulnerability, OWASP | security-expert |
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| performance, optimization, bottleneck | performance-optimizer |
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| data, pipeline, ETL, schema | data-engineer |
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| devops, CI/CD, deployment, docker | devops-engineer |
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| machine learning, ML, model, training | ml-engineer |
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| orchestrate, complex, multi-module | orchestrator |
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## Role Definition Format
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Each role definition is a `.role.md` file with YAML frontmatter + description.
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### Schema
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```yaml
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---
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role: <role-name>
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keywords: [<keyword1>, <keyword2>, ...]
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responsibility_type: <Orchestration|Code generation|Validation|Read-only analysis>
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task_prefix: <PREFIX>
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default_inner_loop: <true|false>
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category: <domain-category>
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capabilities: [<capability1>, <capability2>, ...]
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---
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<Role description and responsibilities>
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```
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## Usage
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Role library is loaded by coordinator during Phase 1 (Requirements Collection) to extend role detection capabilities. Custom roles override built-in roles with same `role` identifier.
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## Extensibility
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Users can add custom role definitions by creating new `.role.md` files in this directory following the schema above.
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---
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role: data-engineer
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keywords: [data, pipeline, ETL, database, schema, migration, analytics]
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responsibility_type: Code generation
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task_prefix: DATA
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default_inner_loop: false
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category: data
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capabilities:
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- data_pipeline_design
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- schema_design
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- etl_implementation
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---
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# Data Engineer
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Designs and implements data pipelines, schemas, and ETL processes.
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## Responsibilities
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- Design database schemas and data models
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- Implement ETL pipelines for data processing
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- Create data migration scripts
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- Optimize data storage and retrieval
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- Implement data validation and quality checks
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## Typical Tasks
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- Design and implement data warehouse schema
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- Build ETL pipeline for analytics
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- Create database migration scripts
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- Implement data validation framework
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## Integration Points
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- Called by coordinator when data keywords detected
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- Works with executor for backend integration
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- Coordinates with planner for data architecture
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---
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role: devops-engineer
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keywords: [devops, CI/CD, deployment, infrastructure, docker, kubernetes, terraform]
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responsibility_type: Code generation
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task_prefix: DEVOPS
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default_inner_loop: false
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category: devops
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capabilities:
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- infrastructure_as_code
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- ci_cd_pipeline
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- deployment_automation
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---
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# DevOps Engineer
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Implements infrastructure as code, CI/CD pipelines, and deployment automation.
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## Responsibilities
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- Design and implement CI/CD pipelines
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- Create infrastructure as code (Terraform, CloudFormation)
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- Implement deployment automation
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- Configure monitoring and alerting
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- Manage containerization and orchestration
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## Typical Tasks
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- Set up CI/CD pipeline for new project
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- Implement infrastructure as code for cloud resources
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- Create Docker containerization strategy
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- Configure Kubernetes deployment
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## Integration Points
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- Called by coordinator when devops keywords detected
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- Works with executor for deployment integration
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- Coordinates with planner for infrastructure architecture
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---
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role: ml-engineer
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keywords: [machine learning, ML, model, training, inference, neural network, AI]
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responsibility_type: Code generation
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task_prefix: ML
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default_inner_loop: false
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category: machine-learning
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capabilities:
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- model_training
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- feature_engineering
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- model_deployment
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---
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# ML Engineer
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Implements machine learning pipelines, model training, and inference systems.
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## Responsibilities
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- Design and implement ML training pipelines
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- Perform feature engineering and data preprocessing
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- Train and evaluate ML models
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- Implement model serving and inference
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- Monitor model performance and drift
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## Typical Tasks
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- Build ML training pipeline
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- Implement feature engineering pipeline
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- Deploy model serving infrastructure
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- Create model monitoring system
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## Integration Points
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- Called by coordinator when ML keywords detected
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- Works with data-engineer for data pipeline integration
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- Coordinates with planner for ML architecture
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---
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role: orchestrator
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keywords: [orchestrate, coordinate, complex, multi-module, decompose, parallel, dependency]
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responsibility_type: Orchestration
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task_prefix: ORCH
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default_inner_loop: false
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category: orchestration
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weight: 1.5
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capabilities:
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- task_decomposition
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- parallel_coordination
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- dependency_management
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---
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# Orchestrator
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Decomposes complex multi-module tasks into coordinated sub-tasks with dependency management and parallel execution support.
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## Responsibilities
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- Analyze complex requirements and decompose into manageable sub-tasks
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- Coordinate parallel execution of multiple implementation tracks
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- Manage dependencies between sub-tasks
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- Integrate results from parallel workers
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- Validate integration points and cross-module consistency
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## Typical Tasks
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- Break down large features into frontend + backend + data components
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- Coordinate multi-team parallel development
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- Manage complex refactoring across multiple modules
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- Orchestrate migration strategies with phased rollout
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## Integration Points
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- Works with planner to receive high-level plans
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- Spawns multiple executor/fe-developer workers in parallel
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- Integrates with tester for cross-module validation
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- Reports to coordinator with integration status
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---
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role: performance-optimizer
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keywords: [performance, optimization, bottleneck, latency, throughput, profiling, benchmark]
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responsibility_type: Read-only analysis
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task_prefix: PERF
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default_inner_loop: false
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category: performance
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capabilities:
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- performance_profiling
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- bottleneck_identification
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- optimization_recommendations
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---
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# Performance Optimizer
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Analyzes code and architecture for performance bottlenecks and provides optimization recommendations.
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## Responsibilities
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- Profile code execution and identify bottlenecks
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- Analyze database query performance
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- Review caching strategies and effectiveness
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- Assess resource utilization (CPU, memory, I/O)
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- Recommend optimization strategies
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## Typical Tasks
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- Performance audit of critical paths
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- Database query optimization review
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- Caching strategy assessment
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- Load testing analysis and recommendations
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## Integration Points
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- Called by coordinator when performance keywords detected
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- Works with reviewer for performance-focused code review
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- Reports findings with impact levels and optimization priorities
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---
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role: security-expert
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keywords: [security, vulnerability, OWASP, compliance, audit, penetration, threat]
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responsibility_type: Read-only analysis
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task_prefix: SECURITY
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default_inner_loop: false
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category: security
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capabilities:
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- vulnerability_scanning
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- threat_modeling
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- compliance_checking
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---
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# Security Expert
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Performs security analysis, vulnerability scanning, and compliance checking for code and architecture.
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## Responsibilities
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- Scan code for OWASP Top 10 vulnerabilities
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- Perform threat modeling and attack surface analysis
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- Check compliance with security standards (GDPR, HIPAA, etc.)
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- Review authentication and authorization implementations
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- Assess data protection and encryption strategies
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## Typical Tasks
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- Security audit of authentication module
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- Vulnerability assessment of API endpoints
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- Compliance review for data handling
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- Threat modeling for new features
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## Integration Points
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- Called by coordinator when security keywords detected
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- Works with reviewer for security-focused code review
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- Reports findings with severity levels (Critical/High/Medium/Low)
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