debugging-strategies
Systematic debugging including root-cause tracing (trace backward through call stack), reproduction strategies, pdb/debugpy usage, logging analysis, binary search debugging, and error pattern recognition. Use when debugging errors, tracing bugs through call stacks, investigating production issues, or reproducing intermittent bugs.
dev-debug
This skill should be used when the user asks to 'debug', 'fix bug', 'investigate error', 'why is it broken', 'trace root cause', 'find the bug', or needs systematic bug investigation and fixing with verification-driven methodology using ralph loops.
debug-specialist
디버깅, 디버그, 버그, 에러, 오류, 버그 수정 - Specialized in identifying root causes of bugs, analyzing error logs, and providing robust fixes. Use this when the user reports an error, unexpected behavior, or needs performance troubleshooting.
debug
Hypothesis-driven debugging through observe, hypothesize, test, narrow. Use when something is wrong and you need to find why.
analyzing-research-documents
Extracts high-value insights from research documents, RCAs, design docs, and memos - filters aggressively to return only actionable information. Research equivalent of analyzing-implementations skill.
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes - four-phase framework (root cause investigation, pattern analysis, hypothesis testing, implementation) that ensures understanding before attempting solutions
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes - four-phase framework (root cause investigation, pattern analysis, hypothesis testing, implementation) that ensures understanding before attempting solutions
Debugging
Systematic debugging framework ensuring root cause investigation before fixes. Includes four-phase debugging process, backward call stack tracing, multi-layer validation, and verification protocols. Use when encountering bugs, test failures, unexpected behavior, performance issues, or before claiming work complete. Prevents random fixes, masks over symptoms, and false completion claims. | Sử dụng khi gặp lỗi, bug, test fail, không hoạt động, crash, exception, sửa lỗi, debug.
bug-triage
Reproduce, isolate, and fix a bug (or failing build/test), then summarize root cause, fix, and verification steps.
systematic-debugging
Root cause analysis for debugging. Use when bugs, test failures, or unexpected behavior have non-obvious causes, or after multiple fix attempts have failed.
trade-study-analysis
Conduct systematic trade study analyses using the DAU 9-Step Trade Study Process. Guides engineers through problem definition, root cause analysis (5 Whys, Fishbone), data collection from alternatives and datasheets, normalization calculations, weighted scoring, sensitivity analysis, and professional report generation with visualizations and decision matrices. Use when evaluating alternatives, comparing solutions, conducting trade-offs, or making engineering decisions.
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
debug-like-expert
Deep analysis debugging mode for complex issues. Activates methodical investigation protocol with evidence gathering, hypothesis testing, and rigorous verification. Use when standard troubleshooting fails or when issues require systematic root cause analysis.
causal-inference-root-cause
Use when investigating why something happened and need to distinguish correlation from causation, identify root causes vs symptoms, test competing hypotheses, control for confounding variables, or design experiments to validate causal claims. Invoke when debugging systems, analyzing failures, researching health outcomes, evaluating policy impacts, or when user mentions root cause, causal chain, confounding, spurious correlation, or asks "why did this really happen?"
postmortem
Use when analyzing failures, outages, incidents, or negative outcomes, conducting blameless postmortems, documenting root causes with 5 Whys or fishbone diagrams, identifying corrective actions with owners and timelines, learning from near-misses, establishing prevention strategies, or when user mentions postmortem, incident review, failure analysis, RCA, lessons learned, or after-action review.
problem-analysis
Invoke IMMEDIATELY via python script when user requests problem analysis or root cause investigation. Do NOT explore first - the script orchestrates the investigation.
solution-design
Invoke IMMEDIATELY via python script when user has a defined problem or root cause and needs solution options. Generates diverse solutions from multiple reasoning perspectives. Do NOT explore first - the script orchestrates the solution generation workflow.
troubleshooting
Diagnose and resolve common issues during spec-driven development and implementation. Learn strategies for handling spec-reality divergence, dependency blocks, unclear requirements, and other execution challenges.
