Which programming languages does this skill support?

It provides references and best practices for Python (Hypothesis), TypeScript/JS (fast-check), Rust (proptest), Go (rapid), Java (jqwik), and Haskell (QuickCheck).

What is Property-Based Testing (PBT)?

PBT is a testing methodology that checks if specific properties (invariants) hold true for all possible inputs, using automated data generation to find edge cases that manual tests might miss.

How does this skill improve Claude's coding ability?

It provides Claude with a structured framework to detect when PBT is applicable and guides it in writing high-quality, non-tautological test suites with proper input strategies.

When should I use PBT over standard unit tests?

PBT is superior for testing serialization, pure functions, data normalizers, and complex algorithms where edge cases are difficult to predict manually.

Property-Based Testing for Claude Code

Name: Property-Based Testing for Claude Code
Author: ed3dai

byed3dai

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安全与测试

Implements robust property-based testing patterns to verify code invariants and detect edge cases across multiple languages.

This skill empowers Claude to move beyond simple example-based unit tests by implementing Property-Based Testing (PBT), a methodology that generates random inputs to verify that specific properties hold true for all cases. It provides a comprehensive property catalog—including roundtrip, idempotence, and commutativity patterns—alongside library-specific syntax for frameworks like Hypothesis, fast-check, and proptest. By using this skill, developers can ensure higher code reliability for serialization, data transformation, and complex algorithmic logic while avoiding common pitfalls like tautological assertions or vacuous test inputs.

主要功能

01Language-specific guidance for major libraries including Hypothesis, fast-check, proptest, and QuickCheck

02Pattern detection to automatically suggest PBT for encoders, decoders, and data normalizers

03Quality checklist to prevent common mistakes like tautological tests or over-filtering inputs

04Comprehensive property catalog for identifying invariants like Roundtrip, Idempotence, and Oracles

05Optimized input strategy best practices for performance and realistic data generation

065 GitHub stars

使用场景

01Testing complex mathematical or logical pure functions against hundreds of generated edge cases

02Validating normalization and sanitization logic through idempotence and invariant checks

03Verifying serialization pairs to ensure data integrity during encode/decode cycles

What are Skills?·How to Install

Install with 🐟 Skill.Fish

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

For use in Claude.ai and ChatGPT

Download Skill