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Found 208 Skills
Debug experiment code with structured error analysis. Categorize errors, apply targeted fixes with retry logic, and use reflection to prevent recurring issues. Use when experiment code fails or produces incorrect results.
Use when encountering bugs or test failures - systematic debugging using debuggers, internet research, and agents to find root cause before fixing
This skill provides expert-level guidance for debugging and fixing bugs in VS Code extensions. Use when investigating runtime errors, fixing memory leaks, resolving WebView issues, debugging activation problems, fixing TypeScript type errors, or troubleshooting extension communication failures. Covers systematic debugging workflows, common bug patterns, root cause analysis, and prevention strategies.
Run blameless post-mortems and retrospectives with root-cause analysis and action tracking.
Utilize AI to assist in testing activities, including test data generation, defect root cause analysis, test prioritization, and intelligent test recommendation. The default output format is Markdown, and you can request Excel/CSV/JSON formats instead. This skill applies to AI-assisted testing scenarios.
Advanced debugging specialist for diagnosing and resolving code issues. Use when user encounters bugs, errors, unexpected behavior, or mentions debugging.
Four-mantra debugging discipline — reproduce, trace the fail path, falsify the hypothesis, cross-reference every breadcrumb. Recite the mantra block verbatim at the start of any debugging session, then apply the four steps in order before proposing any fix. Trigger on /debug-mantra and proactively whenever debugging starts — user reports a bug, says something is broken/throwing/failing, asks to debug/diagnose/investigate an issue, or pastes a stack trace or error log.
Write effective blameless postmortems with root cause analysis, timelines, and action items. Use when conducting incident reviews, writing postmortem documents, or improving incident response processes.
4-phase systematic debugging methodology with root cause analysis and evidence-based verification. Use when debugging complex issues.
Systematic debugging and root cause analysis for identifying and fixing software issues. Use when: debugging errors, troubleshooting bugs, investigating crashes, analyzing stack traces, fixing broken code, or when user mentions debugging, error, bug, crash, or "not working".
Performs root cause analysis on DAG execution failures. Traces failure propagation, identifies systemic issues, and generates actionable remediation guidance. Activate on 'failure analysis', 'root cause', 'why did it fail', 'debug failure', 'error investigation'. NOT for execution tracing (use dag-execution-tracer) or performance issues (use dag-performance-profiler).
Fixes GitHub issues with parallel analysis. Use to debug errors, resolve regressions, fix bugs, or triage issues.