debugging

# Debugging This skill equips an AI agent with a systematic methodology for diagnosing and resolving software bugs. Rather than guessing at fixes, the agent follows a structured process — reproduce, isolate, diagnose, fix, verify — to find root causes and produce reliable corrections. It handles a wide range of bug categories including logic errors, runtime exceptions, race conditions, memory leaks, and performance regressions across multiple languages and runtime environments. ## Workflow 1. **Reproduce the problem.** Confirm the bug is observable and repeatable. Gather the exact error message, stack trace, log output, or description of unexpected behavior. Identify the minimum input or sequence of steps that triggers the issue. If the bug is intermittent, note the frequency and any environmental conditions (load, timing, specific data) that correlate with its appearance. 2. **Isolate the fault location.** Use the stack trace, error message, and code structure to narrow down the region of code responsible. Trace data flow backward from the point of failure to find where the value diverged from expectations. Eliminate unrelated code paths by checking whether the bug persists when components are stubbed out or bypassed. For large codebases, use binary search strategies — disable half the system, check if the bug still occurs, and repeat. 3. **Diagnose the root cause.** Once the faulty region is identified, determine exactly why the code misbehaves. Common root causes incl...