debug

# Debug Helper $ARGUMENTS Systematic debugging for application issues. ## Project context - Recent logs: !`docker compose logs --tail 20 2>/dev/null || tail -20 logs/*.log 2>/dev/null || echo "no-logs-found"` ## Automated Error Parsing Pipe error output through the error parser for structured diagnosis: ```bash # Pipe from failing command your_command 2>&1 | python3 ${CLAUDE_SKILL_DIR}/scripts/error-parser.py # Or from a log file cat /var/log/app/error.log | python3 ${CLAUDE_SKILL_DIR}/scripts/error-parser.py ``` The script outputs JSON with: - **language**: detected language (python/node/go/php) - **error_type**: extracted error class (e.g., ModuleNotFoundError) - **message**: the error message text - **category**: classification (import, reference, type, connection, timeout, memory, permission, syntax) - **stack_frames**: parsed file/line/function from the stack trace - **files_to_check**: unique files from the trace, ordered by relevance - **common_causes**: likely root causes for this error category Use the parsed output to focus investigation on the right files and hypotheses. --- ## Methodology — The Iron Law ``` NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST ``` Random fixes waste time and create new bugs. Quick patches mask underlying issues. Complete each phase before proceeding to the next. ### Phase 1 — Root Cause Investigation Read error messages and stack traces completely. Reproduce reliably (or gather more data — don't guess). Check recent chang...