bmad-testarch-test-review

Assess test quality with TEA knowledge fragments and generate a 0–100 score with prioritized improvements.

Updated Dec 23, 2025
One-click install
npx skills add https://github.com/joekhosbayar/go-mighty --skill bmad-testarch-test-review-joekhosbayar
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: bmad-testarch-test-review
Source: https://github.com/joekhosbayar/go-mighty/tree/main/.gemini/skills/bmad-testarch-test-review
Command: npx skills add https://github.com/joekhosbayar/go-mighty --skill bmad-testarch-test-review-joekhosbayar

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires tomllib, and includes scripts (resource) components.

What problem does it solve?

This Skill provides a structured, TEA-based approach to evaluate and improve test quality by coordinating knowledge fragments, validation checklists, and multi-step workflows to produce actionable recommendations and a reproducible quality score.

Core Features & Use Cases

  • Orchestrates adaptive quality checks across determinism, isolation, maintainability, and performance using modular worker steps.
  • Loads core TEA fragments (test-quality, fixture-architecture, network-first, data-factories, etc.) and applies a standardized evaluation rubric.
  • Generates a 0–100 quality score with a prioritized set of improvements and a comprehensive generate-report workflow for documentation and governance.
  • Supports create/resume/validate/edit modes to manage long-running reviews and maintain traceable progress across runs.

Quick Start

Run a TEA-based test quality review on the current test suite to produce a 0–100 score and a prioritized improvement plan.

Frequently Asked Questions about bmad-testarch-test-review

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

FAQPage Schema
How do I assess test suite quality and generate a score for my test files?

You can assess test suite quality by running a TEA-driven review that evaluates determinism, isolation, and maintainability to generate a 0–100 score. This process uses standardized validation checklists and modular worker steps to produce a prioritized improvement plan.

What does a TEA-based test quality review check for in my test suite?

A TEA-based test quality review checks for test determinism, isolation, maintainability, and performance. It loads core knowledge fragments like fixture-architecture and data-factories, applying a standardized evaluation rubric to validate your test suite against best practices.

How do I run a test quality review on a specific directory or single test file?

To run a test quality review on a single file, directory, or suite, you apply the configured test scope using strict frontmatter-based skill inputs. The review then processes the specified scope to produce actionable recommendations and a comprehensive report.

Can I resume an interrupted test quality review or edit a previous evaluation?

Yes, you can resume or edit a previous test quality evaluation. The review workflow supports create, resume, validate, and edit modes to manage long-running reviews, ensuring traceable progress and maintaining state across multiple runs.

Do I need any specific Python modules to run the TEA test quality checklist workflow?

Yes, the workflow requires the standard Python tomllib module to load configuration. This dependency is necessary to enforce strict frontmatter-based skill inputs and load the core TEA fragments required for the validation checklist.

What's the best way to document test quality scores and improvement plans for governance?

The best way to document test quality scores for governance is to use the generate-report workflow. This produces a comprehensive final report containing the 0–100 quality score and a prioritized set of actionable recommendations for your test suite.