Systematic Debugging

About

The Systematic Debugging skill transforms the way Claude approaches technical issues by enforcing a disciplined root-cause analysis workflow. Instead of guessing or applying 'quick fixes' that might introduce new problems, this skill guides the AI to gather evidence from error logs, reproduce issues reliably, trace data flow, and validate hypotheses before implementing a single, focused fix. It is an essential tool for resolving persistent test failures, architectural inconsistencies, and subtle performance regressions across any tech stack.

Key Features

• Reliable issue reproduction and documentation of failure steps
• Evidence-based root cause analysis using logs and stack traces
• Backward data-flow tracing to isolate the origin of bad values
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• Hypothesis-driven testing to validate assumptions before fixing
• Architectural red-flag detection for fundamental system failures

Use Cases

• Resolving deep-seated bugs where previous 'quick fix' attempts have failed
• Troubleshooting recurring test failures or intermittent build errors
• Identifying the source of unexpected data mutations in complex call stacks