Skip to content
Research
Skill

/code-debugging

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.

From plugin
agent-research-skills
26531 skills1 command
Install
$ npx -y skills add lingzhi227/agent-research-skills --skill code-debugging --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/code-debugging

Context preview

The summary Claude sees to decide when to auto-load this skill.

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.

SKILL.md

code-debugging.SKILL.md
name: code-debugging
description: 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.
argument-hint: [error-or-code]

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

1. Read the error traceback (last 1500 chars if truncated) 2. Identify the exact line and variable causing the error 3. 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: 1. Explain why the error occurred 2. Identify which lines caused it 3. Describe the fix line-by-line 4. 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

Related Skills

  • Upstream: [experiment-code](../experiment-code/)
  • See also: [paper-to-code](../paper-to-code/), [data-analysis](../data-analysis/)
Read more
Ships withagent-research-skills

31 skills for Claude Code covering the full academic research paper lifecycle — from literature search to slide generation — plus GitHub repository analysis for research topics. Extracted from 17 GitHub repos studying LLM-agent-driven research automation.

Get the whole plugin
Stats
282
Stars
34
Forks
Maintained
Maintenance
Python
Language
5mo ago
Last commit
5mo ago
Created

Repo: lingzhi227/agent-research-skills

Other skills on agent-research-skills.