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Found 126 Skills
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.
Evidence-based test debugging enforcing systematic root cause analysis. Use when tests are failing, pytest errors occur, test suite not passing, debugging test failures, or fixing broken tests. Prevents assumption-based fixes by enforcing proper diagnostic sequence. Works with Python (.py), JavaScript/TypeScript (.js/.ts), Go, Rust test files. Supports pytest, jest, vitest, mocha, go test, cargo test, and other frameworks.
Comprehensive A3 one-page problem analysis with root cause and action plan
Use this when encountering any errors, test failures, or unexpected behavior before proposing a fix
Use Sentry MCP to discover, triage, and fix production issues with root-cause analysis. Use when asked to fix Sentry issues, triage production errors, investigate error spikes, or clean up Sentry noise. Requires Sentry MCP server. Triggers on "fix sentry", "triage errors", "production bugs", "sentry issues".
Systematic debugging methodology — binary search isolation, hypothesis-driven debugging, reproducing issues, and root cause analysis. Use when debugging errors, unexpected behavior, or test failures.
Systematic Fishbone analysis exploring problem causes across six categories
Iterative Five Whys root cause analysis drilling from symptoms to fundamentals
Use when errors occur deep in execution and you need to trace back to find the original trigger - systematically traces bugs backward through call stack, adding instrumentation when needed, to identify source of invalid data or incorrect behavior
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.
Root cause analysis for debugging. Use when bugs, test failures, or unexpected behavior have non-obvious causes, or after multiple fix attempts have failed.
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.