0132-debugging-strategies

What problem does it solve?

This Skill turns debugging into a repeatable, evidence-driven workflow so you can quickly isolate root causes for incorrect behavior, crashes, and performance regressions instead of relying on guesswork.

Core Features & Use Cases

• Scientific debugging workflow: Apply observe → hypothesize → experiment → analyze → repeat to converge on root cause.
• Structured investigation phases: Reproduce reliably, gather error and environment signals, form targeted hypotheses, then test and verify changes.
• Practical tooling guidance: Use debugger techniques and language-specific tooling (JavaScript/TypeScript, Python, Go) plus profiling and heap/CPU analysis.
• Advanced regression tactics: Use git bisect, differential comparisons, trace instrumentation, and memory leak detection patterns.
• Use Case: When production errors spike after a release, follow the process to reproduce conditions, compare working vs broken environments, and validate the fix safely.

Quick Start

Use the 0132-debugging-strategies skill to debug a production crash by reproducing the issue, extracting the full stack trace and recent changes, forming a focused hypothesis, and running tests to confirm the root cause.