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Consolidate workflows and tools from commands repository
Repository Restructure: - Move all 83 agent .md files to agents/ subdirectory - Add 15 workflow orchestrators from commands repo to workflows/ - Add 42 development tools from commands repo to tools/ - Update README for unified repository structure The commands repository functionality is now fully integrated, providing complete workflow orchestration and development tooling alongside agents. Directory Structure: - agents/ - 83 specialized AI agents - workflows/ - 15 multi-agent orchestration commands - tools/ - 42 focused development utilities No breaking changes to agent functionality - all agents remain accessible with same names and behavior. Adds workflow and tool commands for enhanced multi-agent coordination capabilities.
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tools/smart-debug.md
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---
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model: claude-sonnet-4-0
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---
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Debug complex issues using specialized debugging agents:
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[Extended thinking: This tool command leverages the debugger agent with additional support from performance-engineer when performance issues are involved. It provides deep debugging capabilities with root cause analysis.]
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## Debugging Approach
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### 1. Primary Debug Analysis
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Use Task tool with subagent_type="debugger" to:
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- Analyze error messages and stack traces
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- Identify code paths leading to the issue
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- Reproduce the problem systematically
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- Isolate the root cause
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- Suggest multiple fix approaches
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Prompt: "Debug issue: $ARGUMENTS. Provide detailed analysis including:
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1. Error reproduction steps
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2. Root cause identification
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3. Code flow analysis leading to the error
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4. Multiple solution approaches with trade-offs
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5. Recommended fix with implementation details"
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### 2. Performance Debugging (if performance-related)
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If the issue involves performance problems, also use Task tool with subagent_type="performance-engineer" to:
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- Profile code execution
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- Identify bottlenecks
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- Analyze resource usage
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- Suggest optimization strategies
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Prompt: "Profile and debug performance issue: $ARGUMENTS. Include:
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1. Performance metrics and profiling data
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2. Bottleneck identification
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3. Resource usage analysis
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4. Optimization recommendations
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5. Before/after performance projections"
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## Debug Output Structure
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### Root Cause Analysis
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- Precise identification of the bug source
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- Explanation of why the issue occurs
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- Impact analysis on other components
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### Reproduction Guide
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- Step-by-step reproduction instructions
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- Required environment setup
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- Test data or conditions needed
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### Solution Options
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1. **Quick Fix** - Minimal change to resolve issue
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- Implementation details
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- Risk assessment
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2. **Proper Fix** - Best long-term solution
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- Refactoring requirements
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- Testing needs
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3. **Preventive Measures** - Avoid similar issues
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- Code patterns to adopt
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- Tests to add
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### Implementation Guide
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- Specific code changes needed
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- Order of operations for the fix
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- Validation steps
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Issue to debug: $ARGUMENTS
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