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Initial commit: SuperClaude v4.0.0 configuration framework
- Core configuration files (CLAUDE.md, RULES.md, PERSONAS.md, MCP.md) - 17 slash commands for specialized workflows - 25 shared YAML resources for advanced configurations - Installation script for global deployment - 9 cognitive personas for specialized thinking modes - MCP integration patterns for intelligent tool usage - Token economy and ultracompressed mode support 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
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.claude/commands/spawn.md
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## Legend
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| Symbol | Meaning | | Abbrev | Meaning |
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|--------|---------|---|--------|---------|
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| → | leads to | | UI/UX | user interface/experience |
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| & | and/with | | auth | authentication |
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| w/ | with | | impl | implementation |
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Execute immediately. Add --plan flag if user wants to see plan first.
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Spawn specialized sub-agent→handle specific task in $ARGUMENTS.
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Thinking flags (optional):
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- --think→multi-agent coordination planning
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- --think-hard→complex agent workflow design
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- --ultrathink→enterprise-scale agent orchestration
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Examples:
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- `/user:spawn --task "optimize database queries" --think` - Spawn data agent w/ coordination analysis
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- `/user:spawn --task "implement auth system" --think-hard` - Complex security impl w/ planning
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- `/user:spawn --task "migrate to microservices" --ultrathink` - Enterprise arch w/ full orchestration
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--task flag:
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- Define clear, focused assignment | Provide necessary context & constraints
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- Set specific success criteria | Establish integration points
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Agent specializations:
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Frontend Agent:
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- UI/UX impl | Component dev
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- State management
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- Performance optimization
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- Accessibility compliance
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Backend Agent:
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- API development
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- Database operations
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- Business logic implementation
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- Integration services
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- Performance tuning
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DevOps Agent:
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- CI/CD pipeline setup
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- Infrastructure automation
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- Deployment strategies
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- Monitoring configuration
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- Security hardening
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Data Agent:
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- Data analysis and transformation
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- Database optimization
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- ETL pipeline development
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- Data quality assurance
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- Reporting solutions
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Best practices for spawning agents:
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1. Define Clear Scope
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- Specific deliverables
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- Clear boundaries
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- Time constraints
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- Quality expectations
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2. Provide Context
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- Relevant code sections
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- Documentation links
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- Previous decisions
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- Technical constraints
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3. Set Success Criteria
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- Measurable outcomes
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- Quality standards
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- Integration requirements
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- Testing expectations
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4. Coordinate Work
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- Avoid conflicts with main work
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- Plan integration points
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- Handle dependencies
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- Manage communication
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Integration workflow:
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1. Spawn agent with clear task definition
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2. Agent works independently on task
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3. Agent provides progress updates
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4. Results reviewed and integrated
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5. Knowledge transferred to main context
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## Benefits & Integration
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Benefits:
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- Parallel task execution
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- Specialized expertise
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- Focused context
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- Reduced cognitive load
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- Faster completion
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Research requirements for agent spawning:
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- Task specialization → Research domain-specific best practices and patterns
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- Agent coordination → WebSearch for multi-agent workflow patterns
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- Integration strategies → C7 documentation for framework-specific integration methods
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- Quality assurance → Must verify agent output validation patterns
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- Never spawn without clear scope - always research coordination patterns
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- All agent instructions must cite sources: // Source: [coordination guide reference]
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Report Output:
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- Agent coordination logs: `.claudedocs/reports/agent-spawn-<timestamp>.md`
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- Task completion summaries: `.claudedocs/summaries/agent-results-<timestamp>.md`
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- Ensure directory exists: `mkdir -p .claudedocs/reports/ .claudedocs/summaries/`
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- Include report location in output: "📄 Agent report saved to: [path]"
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Deliverables: Completed task results from spawned agent, integration plan for merging work, knowledge transfer documentation, coordination summary, and quality validation report.
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