Property based testing

Skill selamy-labs/agent-skills/skills/property-based-testing

Use when example tests can't cover the input space — parsers, serializers, encoders, money math, state machines, anything with a roundtrip or invariant. Assert properties that hold for all inputs, let the framework generate cases and shrink failures to a minimal counterexample.From its SKILL.md

Install

npx -y skills add selamy-labs/agent-skills --skill property-based-testing

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One thing to look at

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SKILL.md

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Property-Based Testing

Example tests check the handful of inputs you thought of. Property-based tests check a property against thousands the framework generates — and when one fails, it shrinks the failure to the smallest input that still breaks, handing you a minimal repro instead of a haystack. Reach for it where the input space is too big to enumerate and a clear invariant exists.

Where it earns its keep

Roundtrips: decode(encode(x)) == x for all x — serializers, parsers, protobuf/JSON codecs, compression.
Invariants: a sorted list is sorted and a permutation of the input; a balance never goes negative; a state machine never reaches an illegal state.
Equivalence / oracle: the fast/new implementation agrees with the slow/reference one for all inputs (the parallel-run check in a rewrite).
Idempotence / commutativity: f(f(x)) == f(x); apply(a,b) == apply(b,a).

Finding the property

The skill is naming the property, not writing the generator. Ask: what must be true regardless of the input? Common shapes — "there and back" (roundtrip), "different path, same result" (oracle/commutativity), "some things never change" (invariant), "doing it twice = doing it once" (idempotence). If you can't state one, the code may not have a crisp contract yet — that's itself a finding.

Shape of a test

from hypothesis import given, strategies as st

@given(st.binary())
def test_roundtrip(payload):
    assert decode(encode(payload)) == payload     # holds for ALL payloads

Discipline

Assert behavior, not the implementation — a property restating the code proves nothing.
Save the shrunk counterexample as a regression example test — property tests find the bug; a pinned example keeps it dead (pairs with regression-ratchet).
Constrain generators to the real domain (valid ranges, encodings) so failures are real bugs, not "we never accept that input anyway."
Don't replace example tests — keep readable examples for the common path; add properties for the space you can't enumerate. They're complementary.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 1 of the 12 instructions most test generation skills give in 496 tokens

Counted across 85 of the 114 authors here whose files we hold, read 2026-09-06

Mock external dependencies in unit testsin 7 of 85
Test behavior, not implementation detailshere, and in 6 of 85
Cover happy path, edge cases, and error casesin 6 of 85
Write the test first and watch it failin 5 of 85
Test mobile, web, and developer APIs separatelyin 4 of 85
Identify the API type and enumerate endpointsin 4 of 85
Check rate limiting on authentication endpointsin 4 of 85
Check all API versionsin 4 of 85
Test all HTTP methods on each endpointin 4 of 85
Test IDOR by changing object identifiersin 4 of 85
Run GraphQL introspection to fetch the schemain 4 of 85
Test SQL injection in JSON parametersin 3 of 85

Said here and by no other author read

let the framework generate and shrink inputs
constrain generators to the real domain

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.