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Found 206 Skills
Systematic workflow for verifying bug fixes to ensure quality and prevent regres...
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?"
Expert at advanced debugging and root cause analysis. Use when troubleshooting complex issues, finding root causes of bugs, investigating performance problems, or analyzing system failures.
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.
Use when encountering errors, bugs, unexpected behavior, or any problem requiring systematic debugging with extended thinking for complex multi-layer issues
Conduct root cause analysis using the Five Whys technique. Use when investigating problems, debugging issues, understanding failures, analyzing churn, or finding the underlying cause of any issue.
Applies a modified Fagan Inspection methodology to systematically resolve persistent bugs and complex issues. Use when multiple previous fix attempts have failed repeatedly, when dealing with intricate system interactions, or when a methodical root cause analysis is needed. Do not use for simple troubleshooting. Triggers after multiple failed debugging attempts on the same complex issue.
Grafana Cloud AI and ML features — Grafana Assistant (natural language queries, dashboard generation, incident investigations), Dynamic Alerting (ML forecasting and outlier detection), Sift (automated root cause analysis with 8 analysis types), Knowledge Graph (entity discovery and RCA Workbench), and the LLM Plugin (OpenAI/Anthropic/Azure integration). Use when setting up AI-powered alerting, using natural language to query metrics/logs, automating incident investigation, or integrating LLMs with Grafana panels and workflows.
Use when debugging bugs, test failures, build failures, performance regressions, or unexpected behavior and you need root-cause investigation before proposing fixes. Trigger on requests to debug, investigate why something broke, or find the source of a technical issue.
Root-cause discipline for bugs, test failures, and unexpected behavior. Embedded grill on the hypothesis before writing fix code. Use when encountering any bug, failing test, or behavior that doesn't match expectation.
Use this whenever you encounter any bugs, test failures, or abnormal behavior, and execute it before proposing a fix
Root cause analysis and debugging protocols. Use when encountering errors, test failures, unexpected behavior, stack traces, or when code behaves differently than expected.