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219ff3905a
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>
151 lines
3.0 KiB
Markdown
151 lines
3.0 KiB
Markdown
# /spawn - Spawn focused agent for specialized tasks
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## Legend
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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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## Syntax
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`/spawn [flags] [task-description]`
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@include shared/flag-inheritance.yml#Universal_Always
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## Core Flags
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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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--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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--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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## Agent Types
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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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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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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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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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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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## Execution Modes
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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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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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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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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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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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- 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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## Examples
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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 |