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auto-test-project

Automate project-level AI testing workflows with multi-round analysis and cross-module quality checks.

47|8|Updated Jan 3, 2026
Search Tags:#templates#verification#quality-assurance#project-management#ai-testing#multi-round#cross-module
One-click install
npx skills add https://github.com/huangwb8/skills --skill auto-test-project
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: auto-test-project
Source: https://github.com/huangwb8/skills/tree/main/auto-test-project
Command: npx skills add https://github.com/huangwb8/skills --skill auto-test-project

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This skill provides a framework for project-level automated testing, enabling multi-round A-round analysis and B-round quality checks across entire projects to systematically identify, document, and remediate cross-module issues.

Core Features & Use Cases

  • Independent A-round evaluation with strict quality gates and traceability across plans and tests
  • Project-wide planning, execution, and documentation for multi-module projects
  • Cross-module issue discovery techniques and structured reporting templates
  • Automated creation of planning and testing skeletons with plan-report consistency enforcement
  • Template-driven verification and artifact generation to support repeatable iterations

Quick Start

Initialize a project session by running the create_test_session.py script to start the A-round workflow.

Frequently Asked Questions about auto-test-project

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

FAQPage Schema
How do I automate project-level AI testing for multi-module applications?▼

Project-level AI testing is automated by running a setup script to initialize a multi-round analysis workflow, enforcing cross-module quality gates, and generating traceable documentation across plans and tests.

What is A-round analysis in cross-module quality assurance?▼

A-round analysis is an independent evaluation phase that systematically discovers cross-module issues, applies strict quality gates, and maintains traceability between planning documents and corresponding test artifacts.

How do I enforce plan-report consistency across testing artifacts?▼

Plan-report consistency is enforced by using a centralized configuration file to drive template-driven generation of planning and testing skeletons, ensuring all iterations produce matching and traceable artifacts.

Do I need a yaml configuration file to run multi-round AI testing workflows?▼

Yes, a yaml configuration file is required. It drives the template-driven verification process, enforces plan-report consistency, and manages the workflow settings for multi-round analysis and quality checks.

How do I generate structured testing skeletons for full project verification?▼

Structured testing skeletons are generated by running the initialization script, which automatically creates templated planning and testing documents to support repeatable iterations and systematic issue discovery.

Are there limitations to using templates for cross-module issue discovery?▼

Template-driven cross-module issue discovery requires strict adherence to enforced plan-report consistency and independent A-round evaluation rules, limiting ad-hoc testing outside the defined configuration boundaries.

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