debugging

Log parsing extracts structured error data from unstructured logs using pattern detection and regex rules. Run the provided Python script (`python scripts/parse-logs.py <logfile>`) to automatically identify errors, extract stack traces, and correlate related events across log entries.

Stack-trace analysis identifies the call sequence and failure point in errors spanning different languages. This Skill applies cross-language pattern matching to parse stack frames, resolve function names, and pinpoint the root cause regardless of whether errors originate in Python, Java, JavaScript, or other languages.

Error reproduction maps observed failure symptoms to code paths and test conditions. The Skill guides you through extracting reproduction steps from logs, creating minimal test cases, applying targeted fixes, and verifying the resolution before deploying to production.

Yes. Pattern-based log analysis works across development, testing, and operations contexts. Extract errors from distributed systems, correlate failures between services, and diagnose production anomalies by detecting patterns in multi-source logs and identifying where failures propagate.

Test-failure debugging identifies error patterns in test output: assertion mismatches, timeout events, resource exhaustion, and dependency failures. Pattern detection flags recurring failure signatures across test runs, enabling root-cause isolation and prevention of flaky tests.

The provided helper scripts handle common log formats and regex patterns, so basic familiarity with logs and error messages is sufficient. For custom log formats, understanding regex syntax and the script structure accelerates pattern customization.