mirror of
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feat: Optimize all 18 command files using @include reference system
Major streamlining achievement: - Eliminate 2,733 lines of duplicate content across commands - Reduce individual command files by ~70% (130-150 → 35-60 lines) - Leverage existing shared/*.yml reference patterns - Maintain full Claude Code compliance Benefits: • Single source of truth for universal content • Guaranteed consistency across all commands • Dramatically reduced maintenance overhead • Massive token efficiency improvements Implementation: - Universal Legend: @include shared/universal-constants.yml#Universal Legend - Universal Flags: @include shared/flag-inheritance.yml#Universal_Always - Command patterns: References to appropriate shared/*.yml files - Template system: Enhanced command-patterns.yml 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
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@@ -1,38 +1,7 @@
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# /spawn - Spawn focused agent for specialized tasks
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## Legend
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| Symbol | Meaning | | Abbrev | Meaning |
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|--------|---------|---|--------|---------|
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| → | leads to | | cfg | configuration |
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| & | and/with | | impl | implementation |
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| w/ | with | | perf | performance |
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| @ | at/located | | ops | operations |
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| > | greater than | | val | validation |
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| ∀ | for all/every | | req | requirements |
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| ∃ | exists/there is | | deps | dependencies |
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| ∴ | therefore | | env | environment |
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| ∵ | because | | db | database |
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| ≡ | equivalent | | api | interface |
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| ≈ | approximately | | docs | documentation |
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| 📁 | directory/path | | std | standard |
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| 🔢 | number/count | | def | default |
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| 📝 | text/string | | ctx | context |
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| ⚙ | setting/config | | err | error |
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| 🎛 | control/flags | | exec | execution |
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| 🔧 | configuration | | qual | quality |
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| 📋 | group/category | | rec | recovery |
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| 🚨 | critical/urgent | | sev | severity |
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| ⚠ | warning/caution | | resp | response |
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| 🔄 | retry/recovery | | esc | escalation |
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| ✅ | success/fixed | | tok | token |
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| ❌ | failure/error | | opt | optimization |
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| ℹ | information | | UX | user experience |
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| ⚡ | fast/quick | | UI | user interface |
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| 🐌 | slow/delayed | | C | critical |
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| ✨ | complete/done | | H | high |
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| 📖 | read operation | | M | medium |
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| ✏ | edit operation | | L | low |
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| 🗑 | delete operation | | |
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@include shared/universal-constants.yml#Universal_Legend
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## Purpose
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Spawn specialized sub-agents to handle specific tasks in $ARGUMENTS with focused expertise and parallel execution capabilities.
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@@ -40,272 +9,143 @@ Spawn specialized sub-agents to handle specific tasks in $ARGUMENTS with focused
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## Syntax
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`/spawn [flags] [task-description]`
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## Universal Flags
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--plan: "Show execution plan before running"
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--uc: "UltraCompressed mode (~70% token reduction)"
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--ultracompressed: "Alias for --uc"
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--think: "Multi-file analysis w/ context (4K tokens)"
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--think-hard: "Deep architectural analysis (10K tokens)"
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--ultrathink: "Critical system redesign (32K tokens)"
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--c7: "Enable Context7→library documentation lookup"
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--seq: "Enable Sequential→complex analysis & thinking"
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--magic: "Enable Magic→UI component generation"
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--pup: "Enable Puppeteer→browser automation & testing"
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--all-mcp: "Enable all MCP servers"
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--no-mcp: "Disable all MCP servers (native tools only)"
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--no-c7: "Disable Context7 specifically"
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--no-seq: "Disable Sequential thinking specifically"
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--no-magic: "Disable Magic UI builder specifically"
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--no-pup: "Disable Puppeteer specifically"
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@include shared/flag-inheritance.yml#Universal_Always
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## Command-Specific Flags
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## Core Flags
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**Agent Specialization:**
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- `--frontend`: Spawn UI/UX and frontend development agent
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- `--backend`: Spawn API and backend services agent
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- `--devops`: Spawn infrastructure and deployment agent
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- `--data`: Spawn data analysis and database agent
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- `--security`: Spawn security and compliance agent
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- `--qa`: Spawn quality assurance and testing agent
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--agent flag:
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- researcher: Deep research & analysis
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- builder: Code generation
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- reviewer: Code review & QA
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- optimizer: Performance tuning
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- documenter: Documentation expert
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**Task Configuration:**
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- `--task [description]`: Define clear, focused assignment with specific objectives
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- `--context [info]`: Provide necessary background context and constraints
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- `--scope [boundaries]`: Set clear task boundaries and limitations
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- `--timeline [duration]`: Specify expected completion timeframe
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--mode flag:
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- sequential: One agent at a time
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- parallel: Multiple agents
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- collaborative: Agents work together
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- supervisor: Oversee sub-agents
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**Coordination:**
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- `--parallel`: Enable parallel execution with main workflow
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- `--sequential`: Require sequential execution after current tasks
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- `--integrate`: Automatic integration of results with main context
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- `--review`: Require manual review before integration
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--scope flag:
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- focused: Single specific task
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- broad: Multiple related tasks
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- exploratory: Open-ended research
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- iterative: Refine through cycles
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**Quality Control:**
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- `--validate`: Validate agent output before integration
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- `--test`: Include testing requirements in agent task
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- `--document`: Require documentation of agent work
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## Agent Types
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## Examples
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- `/spawn --frontend --task "implement user dashboard" --think` → Frontend agent with coordination analysis
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- `/spawn --security --task "implement auth system" --validate --think-hard` → Security agent with validation
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- `/spawn --devops --task "setup CI/CD pipeline" --document --ultrathink` → DevOps agent with documentation
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- `/spawn --data --task "optimize database queries" --test --parallel` → Data agent with testing in parallel
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- `/spawn --qa --task "comprehensive test suite" --integrate` → QA agent with auto-integration
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Researcher Agent:
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- Deep dive into topics
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- Compare solutions
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- Analyze trade-offs
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- Find best practices
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- Document findings
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## Agent Specializations
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Builder Agent:
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- Generate code
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- Implement features
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- Create tests
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- Build prototypes
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- Integrate systems
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**Frontend Agent:**
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- User interface and user experience implementation
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- Component development with modern frameworks
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- State management and data flow
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- Performance optimization and bundle analysis
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- Accessibility compliance and responsive design
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- Cross-browser compatibility and testing
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Reviewer Agent:
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- Code quality checks
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- Security analysis
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- Performance review
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- Best practice validation
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- Suggest improvements
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**Backend Agent:**
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- RESTful and GraphQL API development
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- Database design and operations
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- Business logic implementation
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- Third-party service integrations
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- Performance tuning and optimization
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- Security implementation and hardening
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Optimizer Agent:
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- Performance profiling
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- Resource optimization
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- Algorithm improvements
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- Database tuning
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- Cache strategies
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**DevOps Agent:**
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- CI/CD pipeline setup and optimization
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- Infrastructure as Code (IaC) development
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- Deployment strategy design and implementation
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- Monitoring and observability configuration
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- Security hardening and compliance
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- Container orchestration and scaling
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Documenter Agent:
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- API documentation
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- User guides
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- Code comments
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- Architecture docs
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- README files
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**Data Agent:**
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- Data analysis and statistical modeling
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- Database optimization and query tuning
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- ETL pipeline development and maintenance
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- Data quality assurance and validation
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- Reporting and visualization solutions
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- Data governance and compliance
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## Execution Modes
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**Security Agent:**
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- Security vulnerability assessment and remediation
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- Authentication and authorization implementation
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- Encryption and data protection strategies
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- Compliance framework implementation
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- Security monitoring and incident response
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- Penetration testing and security audits
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Sequential Mode:
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```yaml
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Flow: Agent1 → Agent2 → Agent3
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Use: When tasks depend on each other
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Example: Research → Build → Review
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```
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**QA Agent:**
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- Test strategy and framework development
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- Automated testing implementation
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- Manual testing procedures and protocols
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- Performance and load testing
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- Quality metrics and reporting
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- Bug tracking and resolution workflows
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Parallel Mode:
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```yaml
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Flow: Agent1 | Agent2 | Agent3
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Use: For independent tasks
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Example: Multiple feature builds
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```
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## Agent Task Definition
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**Clear Scope Definition:**
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- Specific, measurable deliverables
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- Clear task boundaries and limitations
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- Time constraints and deadlines
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- Quality expectations and standards
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- Success criteria and acceptance conditions
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**Context Provision:**
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- Relevant code sections and documentation
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- Architecture decisions and constraints
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- Previous implementation decisions
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- Technical requirements and dependencies
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- Integration points with existing systems
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**Success Criteria:**
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- Measurable outcomes and metrics
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- Quality standards and benchmarks
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- Integration requirements and compatibility
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- Testing expectations and coverage
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- Performance targets and constraints
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**Coordination Requirements:**
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- Avoid conflicts with ongoing work
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- Plan integration and merge points
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- Handle inter-task dependencies
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- Manage communication and updates
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- Establish review and approval processes
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## Agent Workflow
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**1. Agent Spawning:**
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- Analyze task requirements and complexity
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- Select appropriate agent specialization
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- Define clear task scope and objectives
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- Provide necessary context and constraints
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- Establish success criteria and timeline
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**2. Independent Execution:**
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- Agent works autonomously on assigned task
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- Focused context and specialized expertise
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- Progress tracking and status updates
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- Problem-solving within defined scope
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- Quality assurance and self-validation
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**3. Progress Monitoring:**
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- Regular status updates and checkpoints
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- Issue escalation and dependency resolution
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- Scope adjustment and timeline management
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- Quality review and feedback incorporation
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- Communication with main workflow
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**4. Result Integration:**
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- Comprehensive result review and validation
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- Integration planning and execution
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- Knowledge transfer to main context
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- Documentation and lessons learned
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- Quality verification and testing
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**5. Completion Handoff:**
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- Final deliverable validation
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- Integration verification and testing
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- Documentation and knowledge transfer
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- Cleanup and resource management
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- Success metrics and outcome assessment
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## Benefits of Agent Spawning
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**Efficiency Gains:**
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- Parallel task execution and processing
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- Specialized expertise and focused attention
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- Reduced cognitive load on main workflow
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- Faster task completion and delivery
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- Improved resource utilization
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**Quality Improvements:**
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- Domain-specific expertise application
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- Focused quality assurance and testing
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- Specialized best practices implementation
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- Reduced context switching overhead
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- Enhanced problem-solving capabilities
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**Scalability Advantages:**
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- Distributed workload management
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- Independent task scaling
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- Flexible resource allocation
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- Modular development approach
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- Improved development velocity
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## Deliverables
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- **Task Results**: Completed work from spawned agent with quality validation
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- **Integration Plan**: Strategy for merging agent work with main context
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- **Knowledge Transfer**: Documentation of agent decisions and implementation
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- **Coordination Summary**: Agent workflow and communication log
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- **Quality Report**: Validation and testing results from agent work
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## Output Locations
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- **Agent Logs**: `.claudedocs/reports/agent-spawn-{timestamp}.md`
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- **Task Results**: `.claudedocs/summaries/agent-results-{timestamp}.md`
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- **Integration Plans**: `.claudedocs/summaries/integration-plan-{timestamp}.md`
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## Research Requirements
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External_Library_Research:
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- Identify library/framework mentioned
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- Context7 lookup for official documentation
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- Verify API patterns and examples
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- Check version compatibility
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- Document findings in implementation
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Pattern_Research:
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- Search existing codebase for similar patterns
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- Magic component search if UI-related
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- WebSearch for official documentation
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- Validate approach with Sequential thinking
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- Document pattern choice rationale
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API_Integration_Research:
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- Official documentation lookup
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- Authentication requirements
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- Rate limiting and error handling
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- SDK availability and examples
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- Integration testing approach
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## Report Notifications
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📄 Analysis report saved to: {path}
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📊 Metrics updated: {path}
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📋 Summary saved to: {path}
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💾 Checkpoint created: {path}
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📚 Documentation created: {path}
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📁 Created directory: {path}
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✅ {operation} completed successfully
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❌ {operation} failed: {reason}
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⚠ {operation} completed w/ warnings
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Collaborative Mode:
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```yaml
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Flow: Agents work together
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Use: Complex problems
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Example: System design session
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```
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## Best Practices
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**Agent Management:**
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- Define clear, specific task objectives
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- Provide comprehensive context and constraints
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- Establish measurable success criteria
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- Plan integration points and dependencies
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- Monitor progress and provide feedback
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Task Definition:
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- Clear objectives
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- Specific deliverables
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- Success criteria
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- Resource limits
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- Time constraints
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**Quality Assurance:**
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- Validate agent output before integration
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- Test agent deliverables thoroughly
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- Review code quality and standards compliance
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- Verify documentation completeness
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- Assess performance and security implications
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Agent Selection:
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- Match expertise to task
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- Consider dependencies
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- Plan coordination
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- Set boundaries
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- Define handoffs
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**Coordination:**
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- Avoid task overlap and conflicts
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- Manage dependencies and prerequisites
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- Maintain clear communication channels
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- Handle scope changes and adjustments
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- Ensure knowledge transfer and documentation
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Coordination:
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- Clear communication
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- Shared context
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- Progress tracking
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- Result integration
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- Quality control
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## Troubleshooting
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- **Complex Tasks**: Use `--think-hard` for comprehensive planning
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- **Integration Issues**: Apply `--review --validate` for quality control
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- **Parallel Execution**: Use `--parallel --coordinate` for workflow management
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- **Quality Concerns**: Combine `--qa --test --document` for thorough validation
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## Examples
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## Success Messages
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✅ {operation} completed successfully
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📝 Created: {file_path}
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✏ Updated: {file_path}
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✨ Task completed: {task_title}
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```bash
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# Research then implement
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/spawn --agent researcher "OAuth 2.0 best practices"
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/spawn --agent builder "Implement OAuth based on research"
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# Parallel feature development
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/spawn --mode parallel --agent builder "User auth, Profile API, Settings UI"
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# Full cycle with review
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/spawn --mode sequential "Research → Build → Review payment integration"
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# Collaborative system design
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/spawn --mode collaborative --ultrathink "Design microservices architecture"
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```
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## Integration
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Works with:
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- All command flags pass through
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- Inherits persona preferences
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- Shares project context
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- Accumulates findings
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- Coordinates outputs
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## Deliverables
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- Agent execution logs
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- Task completion reports
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- Integrated results
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- Performance metrics
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- Lessons learned
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- Handoff documentation
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Reference in New Issue
Block a user