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testing-strategy

Define end-to-end testing strategies for AIDB projects across E2E, integration, unit, and framework layers.

19|2|Updated Dec 1, 2025
Search Tags:#testing#debugging#integration#e2e#mcp#unit
One-click install
npx skills add https://github.com/ai-debugger-inc/aidb --skill testing-strategy-ai-debugger-inc
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: testing-strategy
Source: https://github.com/ai-debugger-inc/aidb/tree/main/.claude/skills/testing-strategy
Command: npx skills add https://github.com/ai-debugger-inc/aidb --skill testing-strategy-ai-debugger-inc

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a comprehensive approach to testing AIDB, prioritizing end-to-end testing, DebugInterface abstraction, and MCP response health standards to ensure reliable, fast feedback.

Core Features & Use Cases

  • E2E-First Testing: Emphasizes end-to-end tests to validate real user workflows.
  • DebugInterface Abstraction: Tests can run against both MCP and direct API via a unified interface.
  • MCP Response Health: Guidelines to validate payload structure, content accuracy, and efficiency.

Quick Start

Start by reviewing the core testing philosophy and then run the main test suite via the dev-cli: ./dev-cli test run -s {suite}. Use the recommended patterns for adding new tests.

Frequently Asked Questions about testing-strategy

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

FAQPage Schema
How do I define an end-to-end testing strategy for AIDB projects?▼

End-to-end testing strategy for AIDB prioritizes real user workflows validated through E2E tests, DebugInterface abstraction for unified MCP and direct API testing, and MCP response health checks. Start with the dev-cli test runner: ./dev-cli test run -s {suite}, then apply recommended patterns for new tests across E2E, integration, unit, and framework layers.

Can I run AIDB tests against both MCP and direct API with the same test suite?▼

Yes. The DebugInterface abstraction enables tests to run against both MCP and direct API through a unified interface, eliminating duplicate test code and simplifying maintenance across testing layers.

What should I validate in MCP responses for AIDB testing?▼

MCP response health validation includes payload structure correctness, content accuracy, and efficiency. These standards ensure reliable feedback and prevent subtle failures in production workflows.

How do I add new tests to an existing AIDB test suite?▼

Follow the recommended patterns for marker-based multi-language testing and shared suites documented in the testing strategy. Use the dev-cli to execute and validate tests across E2E, integration, unit, and framework layers with robust logging for troubleshooting.

Does AIDB testing support marker-based multi-language test patterns?▼

Yes. The testing strategy includes marker-based multi-language testing patterns that work across E2E, integration, unit, and framework layers, enabling shared test suites and consistent validation across diverse code contexts.

What happens when AIDB tests fail—how do I troubleshoot?▼

The testing strategy provides robust logging and failure-troubleshooting guidance integrated across E2E, integration, unit, and framework layers. Review logs via dev-cli and apply DebugInterface tracing to isolate whether failures occur at MCP transport, API logic, or test assertion levels.

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