layered-testing

Name: layered-testing
Availability: InStock
Author: Dagster

Guide Python testing with four layers: unit, integration, business logic, and E2E tests.

Updated Aug 23, 2026

Search Tags:#unit tests #testing #pytest #integration tests #python #e2e #test strategy #mocking #fakes

One-click install

npx skills add https://github.com/dagster-io/erk --skill layered-testing

Or copy as Structured Prompt for Agent▼

Please help me install this Agent Skill.
Skill: layered-testing
Source: https://github.com/dagster-io/erk/tree/main/packages/dot-agent-kit/src/dot_agent_kit/data/kits/layered-testing/skills/layered-testing
Command: npx skills add https://github.com/dagster-io/erk --skill layered-testing

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solves? This skill provides a structured, defense-in-depth testing strategy for Python, eliminating confusion about where to place tests and ensuring comprehensive coverage without sacrificing speed. It helps you build reliable applications by guiding you through effective testing practices.

Core Features & Use Cases:

Four-Layer Strategy: Guides on unit tests for fakes, integration tests with mocking, business logic tests over fakes, and E2E tests, ensuring balanced coverage.
Adapter Architecture: Explains ABC/Real/Fake/DryRun patterns for external system wrappers, making your code more modular and testable.
Anti-Patterns & Workflows: Identifies common testing mistakes and provides step-by-step guides for adding features or fixing bugs, accelerating your development.
Use Case: When adding a new feature, use this skill to determine the optimal testing layer, generate appropriate test structures using fakes, and ensure your tests are fast, reliable, and maintainable, reducing debugging time.

Quick Start: I'm adding a new feature to my Python service. Use the layered-testing skill to guide me on where to put my tests and what patterns to use for fast, reliable testing.