How does this skill help optimize test performance?

It provides guidance on input strategies, such as constraining inputs early in the generation process and setting appropriate size limits to prevent slow test execution.

When is Property-Based Testing better than example-based testing?

PBT excels at testing serialization (encode/decode), pure functions, data validators, and complex data structure operations where edge cases are difficult to manually predict.

Which programming languages does this skill support?

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

What is Property-Based Testing (PBT)?

PBT is a testing methodology where you define general properties (invariants) that should always be true for your code, and the testing framework automatically generates a wide range of random inputs to find edge cases that break those properties.

Property-Based Testing

Name: Property-Based Testing
Author: pbdeuchler

bypbdeuchler

0•

Security & Testing

Enhances software reliability by generating random inputs to verify invariants and edge cases across multiple programming languages.

The Property-Based Testing skill empowers developers to move beyond traditional example-based testing by focusing on logical invariants and automated input generation. It provides a comprehensive catalog of testing properties—such as roundtrips, idempotence, and commutativity—alongside library-specific guidance for frameworks like Hypothesis and fast-check. This skill helps identify subtle bugs and edge cases in complex logic like serialization, data normalization, and pure functions, ensuring robust codebases through systematic pattern detection and rigorous validation strategies.

Key Features

01Input strategy best practices to prevent slow tests and high rejection rates

02Pattern detection to identify high-priority PBT opportunities in your code

03Quality checklist to avoid tautological assertions and vacuous tests

04Comprehensive property catalog including Roundtrip, Idempotence, and Commutativity

050 GitHub stars

06Multi-language library support for Python, JS/TS, Rust, Go, and Java

Use Cases

01Verifying serialization and deserialization logic through roundtrip properties

02Testing data normalization and sanitization functions for idempotence

03Validating complex algorithmic transformations and data structure invariants

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add pbdeuchler/llm-plugins property-based-testing

For use in Claude.ai and ChatGPT

Download Skill