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Found 52 Skills
Test quality inspection framework for reviewing test coverage, identifying gaps, and ensuring comprehensive validation
Detect test smells, overmocking, flaky tests, and coverage issues. Analyze test effectiveness, maintainability, and reliability. Use when reviewing tests or improving test quality.
Go testing patterns for production-grade code: subtests, test helpers, fixtures, golden files, httptest, testcontainers, property-based testing, and fuzz testing. Covers mocking strategies, test isolation, coverage analysis, and test design philosophy. Use when writing tests, improving coverage, reviewing test quality, setting up test infrastructure, or choosing a testing approach. Trigger examples: "add tests", "improve coverage", "write tests for this", "test helpers", "mock this dependency", "integration test", "fuzz test". Do NOT use for performance benchmarking methodology (use go-performance-review), security testing (use go-security-audit), or table-driven test patterns specifically (use go-test-table-driven).
Deep dive on table-driven tests in Go: when to use them, when to avoid them, struct design, subtest naming, advanced patterns like test matrices and shared setup, and refactoring bloated tables into clean ones. Use when writing table-driven tests, refactoring test tables, reviewing table test structure, or deciding whether table-driven is the right approach. Trigger examples: "table-driven test", "table test", "test cases struct", "test matrix", "parametrize tests", "data-driven test", "refactor test table". Do NOT use for general test strategy, mocking, golden files, or fuzz testing (use go-test-quality). Do NOT use for benchmarks (use go-performance-review).
Go error handling patterns, wrapping, sentinel errors, custom error types, and the errors package. Grounded in Effective Go, Go Code Review Comments, and production-proven idioms. Use when implementing error handling, designing error types, debugging error chains, or reviewing error handling patterns. Trigger examples: "handle errors", "error wrapping", "custom error type", "sentinel errors", "errors.Is", "errors.As". Do NOT use for panic/recover patterns in middleware (use go-api-design) or test assertion errors (use go-test-quality).
Test-driven development with Kent Beck's canonical 5-step workflow: Test List, Write Test, Make Pass, Refactor, Repeat. Strict vertical-slice cycles with automatic project detection. Use when the user asks to "write tests first", "use TDD", "red-green-refactor", "test-driven development", "build a feature with TDD", "fix a bug with TDD", wants test-first development for any language or framework, or mentions "tracer bullet" or "vertical slice".
Calculates CRAP (Change Risk Anti-Patterns) score for .NET methods, classes, or files. Use when the user asks to assess test quality, identify risky untested code, compute CRAP scores, or evaluate whether complex methods have sufficient test coverage. Requires code coverage data (Cobertura XML) and cyclomatic complexity analysis. DO NOT USE FOR: writing tests, general test execution unrelated to coverage/CRAP analysis, or general code coverage reporting without CRAP context.
Write high-quality Rust unit tests following best practices. Use when writing new tests, reviewing test code, or improving test quality. Emphasizes clear naming, AAA pattern, isolation, and deployment confidence.
Use when reviewing or scoring AI-generated unit tests/UT code, especially when coverage, assertion effectiveness, or test quality is in question and a numeric score, risk level, or must-fix checklist is needed
Transform passive 'Verify X' test descriptions into active, observable test actions. Use when test ideas lack specificity, use vague language, or fail quality validation. Converts to action-verb format for clearer, more testable descriptions.
Reviews code for quality — architecture conformance, anti-patterns, performance issues, maintainability. Read-only analysis that detects circular dependencies, N+1 queries, dead code, naming violations, and layering breaches. Use when the user asks for a code review, wants feedback on code quality, PR review, tech debt analysis, or architecture conformance checks.
Evaluate test suite quality by introducing code mutations and verifying tests catch them. Use for mutation testing, test quality, mutant detection, Stryker, PITest, and test effectiveness analysis.