Hardening Skill

What It Does

Hardening sharpens what already exists — tests, ISCs, and code — without adding new functionality. Five workflows target test-surface and code-surface robustness: property-based testing via fast-check, mutation testing via Stryker, CRAP-complexity scoring, DRY duplication detection, and acceptance-test mutation that perturbs ISC text to catch fluff.

The Problem

Example-based tests check a handful of inputs the author thought of, so the bugs that survive are the inputs the author didn't think of. A test suite can be green and still be weak. ISCs can read as crisp pass/fail and still be fluff that anything would satisfy. You can't see any of this by reading the tests — you need to test the tests. This skill mechanizes that: property tests express the universal claim and shrink failures to the minimal counterexample, mutation testing proves the suite catches injected bugs, and acceptance-test mutation proves each ISC actually constrains the work.

How It Works

Hardening techniques sharpen what already exists — tests, ISCs, code. They don't add new functionality. Five workflows, all targeting test-surface and code-surface robustness.

Workflow Routing

Workflow	Trigger	File
PropertyTest	property test, property based testing, PBT, fast-check, universal quantified claim, shrink counterexample — pure functions, parsers, serializers, data transforms, invariants	Workflows/PropertyTest.md
MutationTest	mutation test, mutation testing, Stryker, test the tests	— planned, not yet built (stub; see Status)
CrapAnalysis	CRAP score, CRAP analysis, risky undertested code	— planned, not yet built (stub; see Status)
DryAnalysis	DRY scan, jscpd, duplication rot	— planned, not yet built (stub; see Status)
AcceptanceTestMutation	acceptance test mutation, sharpen ISCs, detect fluff ISCs	— planned, not yet built (stub; see Status)

Doctrine

These workflows operate against the existing test surface. PropertyTest doesn't replace bun-test examples — properties express the universal claim, examples are sampled instances of it. MutationTest doesn't replace test authoring — it grades existing tests' robustness. CRAP and DRY don't add tests — they prioritize where to add them. Acceptance-test mutation doesn't add ISCs — it mechanizes the Fluff vs Load-bearing distinction from ISAFormat.md.

All five satisfy the same intent: strengthen the test of the test, the test of the ISC, the test of the code. The unifying frame is meta-test — testing the things that test the system.

Status

Workflow	State	Blocker
PropertyTest	Fully scaffolded (v1.0)	None — ready to use
MutationTest	Stub	Stryker integration; deferred to v6.11.0
CrapAnalysis	Stub	AST walker (oxc or bun build --print-ir)
DryAnalysis	Stub	jscpd wrapper
AcceptanceTestMutation	Stub	ISC text perturbation generator

Integration Points

• Testing Doctrine Rule #11 — names fast-check as the property-testing primitive (LIFEOS/DOCUMENTATION/Testing/TestingDoctrine.md).
• ISA format — new bun-property ISC type with property | generator | runs columns (LIFEOS/DOCUMENTATION/ISA/ISAFormat.md § ISC Type Vocabulary).
• Algorithm — hardening is elected during VERIFY when a run's claims warrant property/mutation depth; spend is discovered from the work (the v6.10.0-era tier-gated proposal predates the 2026-07-11 tier retirement).
• System prompt — Verification Is the Mechanism section at top (LIFEOS/LIFEOS_SYSTEM_PROMPT.md).
• BitterPillEngineering skill — AcceptanceTestMutation is the mechanized form of BPE's "would a smarter model render this rule unnecessary" applied to ISCs.

Gotchas

• fast-check shrinking is deterministic only when the seed is captured. Always pin the seed in a comment when a property fails: // fc seed: 0xdeadbeef.
• numRuns: 1000 is the default budget. Increase to 10000 for invariant-critical properties; lower to 100 for slow generators (custom record types with large constraints).
• Property tests spuriously fail with poorly-constrained generators. Constrain integer ranges, string lengths, and record nesting depth explicitly.
• Properties on impure functions (functions that touch disk, network, clock) are wrong — fast-check generates random inputs but the property must be deterministic given the input. Either mock side effects or extract the pure core.
• Generator over-constraint hides bugs (fc.integer({min: 0, max: 100}) for code that handles all integers). Constrain only what the function actually demands.
• Generator under-constraint produces invalid inputs (fc.string() when the function only accepts ASCII). The property must hold across the function's actual valid input domain, no wider.

Examples

• "Property-test the slug parser" → PropertyTest: express round-trip/idempotence claims as fast-check properties, run 1000 random inputs, pin the seed on any failure.
• "What bugs are my example tests missing?" → PropertyTest candidate detection: scan for pure functions (parsers, serializers, transforms) with only example coverage.
• "Mutation-test the hooks suite" → MutationTest is a stub (see Status) — not runnable yet; don't promise kill-rate numbers.