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agentic-quality-engineering

Orchestrate AI agents for test generation, execution, coverage analysis, and quality gating.

1|Updated Dec 29, 2025
Search Tags:#automation#testing#ci/cd#ai agents#quality engineering#fleet coordination
One-click install
npx skills add https://github.com/aquariuscook/Agent_Modus_Map --skill agentic-quality-engineering-aquariuscook
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agentic-quality-engineering
Source: https://github.com/aquariuscook/Agent_Modus_Map/tree/main/.claude/skills/agentic-quality-engineering
Command: npx skills add https://github.com/aquariuscook/Agent_Modus_Map --skill agentic-quality-engineering-aquariuscook

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill enables the use of AI agents to significantly enhance and scale Quality Engineering (QE) processes, acting as force multipliers for human expertise.

Core Features & Use Cases

  • Autonomous Testing: Agents can generate, execute, and analyze tests with minimal human oversight.
  • Fleet Coordination: Manages a fleet of specialized QE agents for comprehensive quality assurance.
  • PACT Principles: Implements Proactive analysis, Autonomous operation, Collaborative feedback, and Targeted risk focus.
  • Use Case: Automate the generation and execution of regression tests for a new code commit, analyze coverage gaps, and provide a quality gate decision before deployment.

Quick Start

Use the agentic-quality-engineering skill to run the full PR quality pipeline for the current code changes.

Frequently Asked Questions about agentic-quality-engineering

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

FAQPage Schema
How do I automate test generation and execution for CI/CD pipelines using AI agents?▼

AI agents automate test generation and execution within CI/CD pipelines by orchestrating a fleet of specialized agents to handle regression tests, analyze coverage gaps, and provide quality gate decisions before deployment.

What is fleet coordination for quality engineering and how does it work?▼

Fleet coordination manages a fleet of specialized QE agents to perform comprehensive quality assurance tasks. It applies PACT principles—proactive analysis, autonomous operation, collaborative feedback, and targeted risk focus—using persistent memory for state management.

Can I use autonomous AI agents to analyze test coverage gaps and enforce quality gates?▼

Yes, autonomous agents can generate, execute, and analyze tests with minimal human oversight. They analyze coverage gaps and provide quality gate decisions for code commits, acting as force multipliers for human quality engineering expertise.

Do I need specific frameworks to run multi-agent coordination for continuous deployment?▼

The skill uses a multi-agent coordination framework with persistent memory for learning and state management. It requires adherence to PACT principles and applies to continuous integration and deployment pipelines to increase deployment frequency.

What are the limitations of using autonomous AI agents for regression testing?▼

While autonomous agents handle test generation, execution, and coverage analysis with minimal oversight, they require a multi-agent coordination framework with persistent memory. Quality gating depends on the PACT principles of proactive analysis and targeted risk focus.

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