testing-strategies

Develop test strategies mapping test types to application layers across Java, Python, and Go.

6|1|Updated Mar 30, 2026

Search Tags:#unit tests #testing #pytest #integration tests #test strategy #e2e testing #junit 5

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npx skills add https://github.com/wesleyosantos91/multi-agents --skill testing-strategies-wesleyosantos91

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: testing-strategies
Source: https://github.com/wesleyosantos91/multi-agents/tree/main/devin/.devin/skills/testing-strategies
Command: npx skills add https://github.com/wesleyosantos91/multi-agents --skill testing-strategies-wesleyosantos91

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It solves the problem of unclear or inconsistent test planning by mapping test types to the layer being tested, so coverage matches real risk and behavior.

Core Features & Use Cases

Test pyramid by code scope: guides when to use Unit, Integration, and E2E tests based on cost, speed, and criticality.
Layer-specific strategies: provides concrete approaches for domain logic, HTTP handlers/controllers, persistence (repositories), messaging (consumers/producers), and external HTTP clients.
Language-aligned examples: shows idiomatic patterns for Java (JUnit 5), Python (pytest), and Go (table-driven tests).
Anti-pattern guardrails: highlights common mistakes like over-mocking, testing implementation details, and fragile tests.

Quick Start

Use this when you need to improve test coverage for a service and want to define a practical testing strategy across unit and integration layers for your codebase.

Frequently Asked Questions about testing-strategies

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I choose the right unit and integration tests for my application layers?▼

Choosing the right unit and integration tests requires mapping test types to specific application layers, ensuring coverage matches real risk. You select tests based on cost, speed, and criticality, applying distinct strategies for domain logic, HTTP boundaries, and persistence layers.

What is the best way to structure a testing strategy across Java, Python, and Go?▼

Structuring a testing strategy across Java, Python, and Go involves defining a testing pyramid and using idiomatic patterns like JUnit 5, pytest, and table-driven tests. This approach aligns test types with code scope, reducing fragile coverage and validating behaviors effectively.

How do I avoid anti-patterns like over-mocking when testing domain logic?▼

Avoiding over-mocking when testing domain logic requires focusing on validating expected behaviors and error cases rather than testing implementation details. By mapping integration points correctly and applying anti-pattern guardrails, you prevent fragile tests and ensure coverage targets real risk.

Does this testing strategy work for messaging workflows and external HTTP clients?▼

Yes, this testing strategy works for messaging workflows and external HTTP clients by providing layer-specific approaches. It validates expected behaviors for consumers, producers, and external interactions, ensuring test coverage matches the real risk of these specific integration points.

When should I use E2E testing instead of unit tests for my HTTP boundaries?▼

You should use E2E testing instead of unit tests for HTTP boundaries when criticality justifies the higher cost and slower speed. Defining a testing pyramid helps balance these factors, guiding when to select broader end-to-end tests over faster unit tests for controllers.