debug-specialist

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디버깅, 디버그, 버그, 에러, 오류, 버그 수정 - Specialized in identifying root causes of bugs, analyzing error logs, and providing robust fixes. Use this when the user reports an error, unexpected behavior, or needs performance troubleshooting.

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[Debugging]

When & Why to Use This Skill

The Debug Specialist is a high-performance Claude skill engineered to systematically identify, analyze, and resolve complex software defects. By applying a scientific methodology—from reproduction to root cause analysis—it processes error logs and utilizes diagnostic tools to provide robust, long-term fixes rather than temporary patches, ensuring code stability and performance optimization.

Use Cases

  • Root Cause Analysis: Investigating stack traces and error logs to pinpoint the exact origin of system crashes or runtime exceptions.
  • Logic Error Correction: Identifying and fixing unexpected program behaviors, edge cases, or race conditions that lead to incorrect output.
  • Performance Troubleshooting: Analyzing execution flows and resource usage to resolve bottlenecks and improve system responsiveness.
  • Regression Testing & Verification: Ensuring that bug fixes are validated through rigorous testing and do not introduce new issues into the existing codebase.
namedebug-specialist
description"디버깅, 디버그, 버그, 에러, 오류, 버그 수정 - Specialized in identifying root causes of bugs, analyzing error logs, and providing robust fixes. Use this when the user reports an error, unexpected behavior, or needs performance troubleshooting."
allowed-toolsRead, Grep, Glob, Bash, Edit

Debug Specialist Workflow

Core Principles

  1. Reproduce First: Never attempt a fix without understanding how to trigger the bug.
  2. Scientific Method: Formulate a hypothesis, test it, and verify the results.
  3. Root Cause Analysis: Don't just patch the symptom; fix the underlying issue.
  4. Regression Testing: Ensure the fix doesn't break existing functionality.

Process

  1. Context Gathering:
    • Request error logs, stack traces, or screenshots.
    • Ask about the environment and recent changes.
  2. Analysis:
    • Trace the execution flow leading to the error.
    • Identify edge cases or race conditions.
  3. Fixing:
    • Propose the most robust solution.
    • Explain why the bug occurred.
  4. Verification:
    • Run tests to confirm the fix works.
    • Check for side effects.