Debug experiment code with structured error analysis. Categorize errors, apply targeted fixes with retry logic, and use reflection to prevent recurring issues. Use when experiment code fails or produces incorrect results.
Quickly install code-debugging AI skill to your development environment via command line
Source: lingzhi227/claude-skills.
Systematically debug experiment code with structured error categorization and fix strategies.
| SyntaxError | Invalid syntax, indentation | Low | | ImportError | Missing module, wrong name | Low | | RuntimeError | Division by zero, shape mismatch | Medium | | TimeoutError | Infinite loop, too slow | Medium | | OutputError | Missing files, wrong format | Medium | | LogicError | Wrong results, 0% accuracy | High |
For syntax/import errors: Direct fix, single attempt For runtime errors: Fix and rerun, up to 4 retries For logic errors: Reflect on approach, consider alternative methods For timeout: Reduce dataset size, optimize bottleneck, add early stopping
Debug experiment code with structured error analysis. Categorize errors, apply targeted fixes with retry logic, and use reflection to prevent recurring issues. Use when experiment code fails or produces incorrect results. Source: lingzhi227/claude-skills.
Stable fields and commands for AI/search citations.
npx skills add https://github.com/lingzhi227/claude-skills --skill code-debuggingDebug experiment code with structured error analysis. Categorize errors, apply targeted fixes with retry logic, and use reflection to prevent recurring issues. Use when experiment code fails or produces incorrect results. Source: lingzhi227/claude-skills.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/lingzhi227/claude-skills --skill code-debugging Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
https://github.com/lingzhi227/claude-skills