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---
name: pairwise-tests
-description: Generate a minimal test matrix covering all pairwise parameter interactions using PICT (Pairwise Independent Combinatorial Testing). Given a function, feature, or configuration space with many input parameters, identifies parameters + value partitions + inter-parameter constraints, builds a PICT model, and produces a small set of test cases (typically 80-99% fewer than exhaustive) that still hits every 2-way combination of parameter values. Empirically catches 60-90% of combinatorial bugs. Use when a function has 3+ parameters with multiple values each and exhaustive testing would explode (feature flag combinations, permission/role matrices, config matrices, multi-field form validation, API parameter spaces). Do NOT use for functions with 1-2 parameters (just write the cases directly), for regulated contexts where provably exhaustive coverage is required (document as an ADR and write all cases), or for testing non-parametric behavior (happy path, single error case, performance regression — use `/add-tests` for those). Output: PICT model, markdown table of generated test cases, expected result per row. See also `/add-tests` for standard test generation and `testing.md` for the Normal/Boundary/Error category discipline.
+description: Generate a minimal test matrix covering all pairwise parameter interactions using PICT (Pairwise Independent Combinatorial Testing). Identifies parameters, value partitions, inter-parameter constraints; builds a PICT model; produces a small set of test cases (typically 80-99% fewer than exhaustive) that still hits every 2-way combination. Empirically catches 60-90% of combinatorial bugs. Use when a function has 3+ parameters with multiple values each and exhaustive testing would explode (feature-flag combos, permission/role matrices, config matrices, multi-field form validation, API parameter spaces). Do NOT use for functions with 1-2 parameters (write cases directly), regulated contexts requiring provably exhaustive coverage (document as ADR and write all cases), or non-parametric behavior (happy path, single error, perf regression — use `/add-tests`). Output: PICT model, markdown table, expected result per row. See `/add-tests` and `testing.md`'s Normal/Boundary/Error.
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# Pairwise Tests (PICT)