How does this skill help with test performance?

It provides 'Input Strategy Best Practices' to help you build constraints directly into your data generators rather than using filters, which significantly speeds up test execution.

Which programming languages are supported?

The skill provides patterns and syntax for Python (Hypothesis), TypeScript/JS (fast-check), Rust (proptest), Go (rapid), Java (jqwik), and Haskell (QuickCheck).

When should I use PBT instead of standard unit tests?

PBT is most effective for pure functions, serialization logic, validators, and complex algorithms where edge cases are difficult to manually enumerate.

What is property-based testing?

Unlike example-based tests that use specific inputs, property-based testing (PBT) generates random inputs to verify that specific invariants—rules that should always be true—hold across all possible data.

Property-Based Testing

Name: Property-Based Testing
Author: ed3dai

byed3dai

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Security & Testing

Automates the identification and implementation of property-based testing patterns to verify code invariants and catch edge cases.

This skill empowers developers to move beyond traditional example-based testing by providing a structured framework for Property-Based Testing (PBT). It offers a comprehensive catalog of mathematical and logical properties—such as idempotence, roundtrips, and commutativity—alongside specific implementation patterns for major libraries like Hypothesis and fast-check. By guiding users through strategy construction, strength hierarchies, and quality checklists, it ensures thorough test coverage and prevents common PBT pitfalls like tautological assertions or vacuous inputs.

Key Features

01Comprehensive property catalog including Roundtrip, Idempotence, and Oracle patterns

0245 GitHub stars

03Quality checklist to identify tautological assertions and missing edge cases

04Automatic pattern detection for serialization, validation, and normalization logic

05Optimized input strategy guidance to minimize test slowness and rejection rates

06Multi-language library support for Python, TypeScript, Rust, Go, and more

Use Cases

01Verifying that sanitization and normalization functions are idempotent and stable

02Refactoring core algorithms by comparing new implementations against trusted reference oracles

03Ensuring data integrity in complex serialization and deserialization (encode/decode) cycles

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add ed3dai/ed3d-plugins property-based-testing

For use in Claude.ai and ChatGPT

Download Skill