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agentic-workflow

Coordinate specialized agents through research, planning, TDD implementation, and review stages.

8|1|Updated Jan 4, 2026
Search Tags:#software engineering#TDD#AI development#multi-agent#orchestration#agentic workflow
One-click install
npx skills add https://github.com/scooter-lacroix/Maestro --skill agentic-workflow
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agentic-workflow
Source: https://github.com/scooter-lacroix/Maestro/tree/main/maestro/skills/agentic-workflow
Command: npx skills add https://github.com/scooter-lacroix/Maestro --skill agentic-workflow

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill provides a structured, multi-agent pipeline for complex implementation tasks, ensuring consistency and traceability in AI-assisted software development.

Core Features & Use Cases

  • Multi-Stage Processing: Orchestrates a sequence of specialized agents (research, planning, validation, implementation, review) for robust task completion.
  • Cache-Based Handoff: Utilizes a defined directory structure for inter-agent communication, ensuring data persistence and clarity.
  • TDD Enforcement: Integrates Test-Driven Development principles into the implementation phase.
  • Use Case: Automate the process of refactoring a specific module in a codebase by having agents research best practices, plan the changes, implement them with tests, and finally review the outcome.

Quick Start

Use the agentic-workflow skill to research, plan, implement, and review a given task.

Frequently Asked Questions about agentic-workflow

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

FAQPage Schema
How do I orchestrate multi-agent AI workflows for software development?▼

Multi-agent AI workflows are orchestrated by coordinating specialized agents through research, planning, validation, implementation, and review stages to ensure structured and traceable AI-assisted software development.

Can I enforce Test-Driven Development in an AI-assisted coding process?▼

Test-Driven Development is enforced during the implementation phase of the agentic workflow, where specialized agents integrate TDD principles to ensure robust, validated code completion.

How does inter-agent communication work in a multi-agent pipeline?▼

Inter-agent communication in a multi-agent pipeline works through a cache-based handoff using a defined directory structure, ensuring data persistence and clarity between the research, planning, and review stages.

What is the best way to automate module refactoring with AI agents?▼

Automating module refactoring is best handled by a multi-stage agentic workflow where agents research best practices, plan changes, implement them with TDD, and review the final outcome automatically.

Does multi-agent orchestration require external dependencies?▼

Multi-agent orchestration requires no external dependencies, operating independently to coordinate specialized agents for robust task completion without prerequisite package installations.

When should I use a structured multi-agent pipeline for AI development?▼

A structured multi-agent pipeline should be used for complex AI implementation tasks that require consistency, traceability, and robust coordination across research, validation, and review stages.

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