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Found 87 Skills
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
Systematic debugging frameworks for finding and fixing bugs - includes root cause analysis, defense-in-depth validation, and verification protocols
Guide Test-Driven Development workflow (Red-Green-Refactor) for new features, bug fixes, and refactoring. Identifies test improvement opportunities and applies pytest best practices. Use when writing tests, implementing features, or following TDD methodology. **PROACTIVE ACTIVATION**: Auto-invoke when implementing features or fixing bugs in projects with test infrastructure (pytest files, tests/ directory). **DETECTION**: Check for tests/ directory, pytest.ini, pyproject.toml with pytest config, or test files. **USE CASES**: Writing production code, fixing bugs, adding features, legacy code characterization.
Investigate, fix, postmortem, prevent. Full incident lifecycle from bug report to systemic prevention. Use when: production down, critical bug, incident response, post-incident review. Composes: /investigate, /fix, /postmortem, /codify-learning.
Test-driven development using Red-Green-Refactor for bug fixes, new features, and regression prevention. Writes a failing test first to prove a defect or define behavior, then implements minimal code to pass, then refactors. Use when fixing bugs, encountering failing behavior, adding new features, writing tests, or when the user mentions TDD, red-green-refactor, regression test, failing test, test first, or test-driven.
Systematic 4-phase debugging with root cause investigation. Use when fixing bugs to prevent random fixes.
Test-Driven Development workflow with session integration. Use when implementing features/bugfixes to enforce RED-GREEN-REFACTOR discipline. Integrates with session-management for enhanced TDD session tracking, checkpoints, and metrics.
Guide for debugging and fixing bugs in the OCaml garbage collector, particularly memory management issues in the runtime's sweeping and allocation code. This skill applies when working on OCaml runtime C code, investigating segfaults in GC operations, or fixing pointer arithmetic bugs in memory managers with size-classed pools and run-length encoding.
Systematic approach to diagnosing and fixing failing tests in Rust projects. Use when tests fail and you need to diagnose root causes, fix async/await issues, handle race conditions, or resolve database connection problems.
Use when implementing any feature or bugfix, before writing implementation code
Fixes GitHub issues with parallel analysis. Use to debug errors, resolve regressions, fix bugs, or triage issues.
Use when a program crashes, a test fails, or code produces wrong results and reading the source isn't enough to see why. Lets you pause execution at any line and inspect the actual runtime state, variable values, types, call stacks, to find what went wrong.