code-debugging

Debug experiment code with structured error analysis. Categorize errors, apply targeted fixes with retry logic, and use reflection to prevent recurring issues.…

INSTALLATION
npx skills add https://github.com/lingzhi227/agent-research-skills --skill code-debugging
Run in your project or agent environment. Adjust flags if your CLI version differs.

SKILL.md

Code Debugging

Systematically debug experiment code with structured error categorization and fix strategies.

Input

  • $0 — Error message, stderr output, or code file with issues
  • $1 — Optional: the code that produced the error

References

  • Debug patterns and state machine: ~/.claude/skills/code-debugging/references/debug-patterns.md

Workflow

Step 1: Categorize the Error

Category

Examples

Severity

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

Step 2: Analyze Root Cause

  • Read the error traceback (last 1500 chars if truncated)
  • Identify the exact line and variable causing the error
  • Check for common patterns:
  • Device mismatch (CPU vs GPU tensors)
  • Shape mismatch in matrix operations
  • Missing data normalization
  • Off-by-one errors in indexing
  • Incorrect loss function for task type

Step 3: Apply Fix Strategy

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

Step 4: Reflect and Prevent

After fixing:

  • Explain why the error occurred
  • Identify which lines caused it
  • Describe the fix line-by-line
  • Note patterns to avoid in future code

Fix Strategy State Machine

Stage 0 (first attempt) → repost code as fresh

Stage 1 (second attempt) → repost or leave depending on severity

Stage 2 (third attempt) → regenerate from scratch if still failing

Rules

  • Prefer minimal targeted edits over full rewrites
  • Maximum 4-5 fix attempts before changing approach
  • Always truncate long error outputs to last 1500 characters
  • After fixing, verify the fix doesn't introduce new errors
  • Keep error history to avoid repeating the same mistakes
  • If 0% accuracy: check accuracy calculation first, then check data pipeline

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