What is 'test gaming' and how does this skill prevent it?

Test gaming occurs when an AI writes code that specifically satisfies its own test cases without correctly implementing logic. This skill prevents it by using separate agents for test generation and implementation.

Which testing frameworks are supported?

It is framework-agnostic and works with major tools like Jest, Vitest, pytest, Playwright, and Cypress, provided they are configured in your repository.

What test coverage targets can I expect?

The skill is designed with an 80% coverage gate as a minimum requirement and provides specialized workflows to reach a target of 95% or higher.

Does this skill support property-based testing?

Yes, it includes specific workflows for generating property-based tests using libraries like fast-check or Hypothesis to validate invariants.

Multi-AI Testing

Name: Multi-AI Testing
Author: adaptationio

byadaptationio

0•

보안 및 테스팅

Implements test-driven development workflows with independent verification to ensure high-quality code and comprehensive test coverage.

Multi-AI Testing is a specialized capability designed to eliminate test gaming and ensure robust software quality through independent verification. By separating the agent that writes tests from the agent that performs the implementation, it prevents code overfitting and ensures that software meets real-world requirements. This skill automates the complete TDD lifecycle, including specification analysis, multi-layered test generation (Unit, Integration, E2E, and Property-based), coverage validation, and AI-powered edge case discovery to consistently achieve coverage targets between 80% and 95%.

주요 기능

01Independent multi-agent verification to prevent test gaming and overfitting

02Multi-tier test generation for unit, integration, and E2E scenarios

03AI-powered edge case discovery and property-based testing

04Coverage validation targeting ≥80% gate and ≥95% comprehensive coverage

050 GitHub stars

06Automated TDD workflows including Test-Fail-Implement-Pass cycles

사용 사례

01Preventing AI agents from writing biased code through independent verification

02Generating high-coverage test suites for legacy codebases with low visibility

03Enforcing strict TDD workflows for mission-critical software components

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add adaptationio/skrillz multi-ai-testing

For use in Claude.ai and ChatGPT

Download Skill