Can this skill handle race conditions and timing issues?

Yes, it is specifically optimized for deep analysis of non-deterministic bugs like race conditions, timing issues, and memory leaks.

How do I trigger the debugging workflow?

You can trigger the skill using natural language commands such as 'codex debug', 'codex root cause', or 'have codex investigate this bug'.

Does it provide the actual code to fix the bug?

Yes, the final output includes a 'Recommended Fix' section which provides specific code changes necessary to resolve the identified root cause.

What makes Codex Debug different from standard debugging?

Codex Debug uses a systematic four-step workflow and high-reasoning AI effort to analyze complex dependencies and logical errors that standard linting or basic AI prompts might miss.

Codex Debug & Root Cause Analysis

Name: Codex Debug & Root Cause Analysis
Author: kanlanc

bykanlanc

セキュリティとテスト

Conducts high-reasoning, systematic debugging and root cause analysis to resolve complex software errors and performance issues.

概要

The Codex Debug skill empowers Claude with a structured methodology for troubleshooting sophisticated technical challenges. By leveraging high-effort reasoning, it meticulously gathers context from error messages and stack traces to evaluate potential failure points. This skill is particularly effective for diagnosing non-obvious issues such as race conditions, memory leaks, and mysterious runtime errors, providing developers with a clear investigation log and actionable code-based fix recommendations.

主な機能

Multi-hypothesis evaluation to determine the primary cause
0 GitHub stars
Automated context gathering from error logs and stack traces
High-reasoning effort execution for complex problem solving
Actionable fix recommendations with specific code implementations
Systematic four-step root cause analysis (RCA) methodology

ユースケース

Troubleshooting intermittent race conditions or complex timing-based bugs
Investigating performance regressions or memory leaks in production code
Deciphering cryptic error messages or deep stack traces in unfamiliar codebases

概要

主な機能

Multi-hypothesis evaluation to determine the primary cause
0 GitHub stars
Automated context gathering from error logs and stack traces
High-reasoning effort execution for complex problem solving
Actionable fix recommendations with specific code implementations
Systematic four-step root cause analysis (RCA) methodology

ユースケース

Troubleshooting intermittent race conditions or complex timing-based bugs
Investigating performance regressions or memory leaks in production code
Deciphering cryptic error messages or deep stack traces in unfamiliar codebases