intermittent-issue-debugging
Debug issues that occur sporadically and are hard to reproduce. Use monitoring and systematic investigation to identify root causes of flaky behavior.
log-analysis
Analyze application and system logs to identify errors, patterns, and root causes. Use log aggregation tools and structured logging for effective debugging.
performance-regression-debugging
Identify and debug performance regressions from code changes. Use comparison and profiling to locate what degraded performance and restore baseline metrics.
root-cause-analysis
Conduct systematic root cause analysis to identify underlying problems. Use structured methodologies to prevent recurring issues and drive improvements.
convening-experts
Convenes expert panels for problem-solving. Use when user mentions panel, experts, multiple perspectives, MECE, DMAIC, RAPID, Six Sigma, root cause analysis, strategic decisions, or process improvement.
crash-debugging
Crash log analysis, symbolication, and debugging workflows for iOS apps. Use when investigating app crashes, analyzing crash reports, symbolicating stack traces, or identifying root causes. Covers crash log retrieval, symbolication with dSYM files, stack trace analysis, and common crash patterns.
debug
Systematic debugging with structured reproduction and root cause analysis.
scalability-advisor
Guidance for scaling systems from startup to enterprise scale. Use when planning for growth, diagnosing bottlenecks, or designing systems that need to handle 10x-1000x current load.
ci-fix
Fix GitHub Actions CI failures using GitHub CLI (gh): inspect runs/logs, identify root cause, patch workflows/code, rerun jobs, and summarize verification. Use when GitHub Actions CI is failing or needs diagnosis.
bug-triage
Reproduce, isolate, and fix a bug (or failing build/test), then summarize root cause, fix, and verification steps. Use when the user reports a bug, regression, or failing build/test and wants a fix.
ci
Diagnoses and fixes CI/CD pipeline failures. Use when user mentions 'CI', 'GitHub Actions', 'GitLab CI', 'ビルドエラー', 'テスト失敗', 'パイプライン', 'CIが落ちた', or asks to analyze build/test failures. Do NOT load for: ローカルビルド, 通常の実装作業, レビュー, セットアップ.
troubleshoot
Guides diagnosis and resolution when problems occur. Use when user mentions 動かない, エラーが出た, 壊れた, うまくいかない, broken, doesn't work, error. Do NOT load for: 正常なビルド, 新機能実装, レビュー.
systematic-debugging
4-phase systematic debugging methodology with root cause analysis and evidence-based verification. Use when debugging complex issues.
Observability-First Debugging
Systematic debugging methodology that eliminates guessing and speculation. Add instrumentation to gather specific data that fully explains the problem. Evidence before hypothesis. Observation before solution.
debugging-workflows
Debug workflow execution issues including syntax errors, agent failures, variable problems, and execution errors. Use when workflows fail, produce unexpected results, or user asks for debugging help.
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.
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