team-arch-opt

Analyze codebase architecture and orchestrate refactoring workflows with validation and review.

76|5|Updated Jul 7, 2026
One-click install
npx skills add https://github.com/catlog22/pi-maestro-flow --skill team-arch-opt-catlog22
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: team-arch-opt
Source: https://github.com/catlog22/pi-maestro-flow/tree/main/.pi/skills/team-arch-opt
Command: npx skills add https://github.com/catlog22/pi-maestro-flow --skill team-arch-opt-catlog22

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill turns architecture refactoring work from a single-threaded effort into a coordinated multi-agent workflow, helping you analyze large codebases, plan changes safely, implement them with less friction, and validate the results.

Core Features & Use Cases

  • Architecture analysis: Detect coupling, cycles, layering issues, dead code, and other structural problems in a codebase.
  • Refactoring planning: Convert findings into a prioritized, measurable refactoring plan with clear ownership and success criteria.
  • Parallel implementation and verification: Coordinate refactor, validation, and review steps across single, fan-out, or independent pipelines.
  • Use case: Use this Skill when a codebase has tangled dependencies or a risky module structure and you want a guided path from diagnosis to verified improvement.

Quick Start

Use the team-arch-opt skill to analyze this repository’s architecture and produce a prioritized refactoring plan with validation and review steps.

Frequently Asked Questions about team-arch-opt

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

FAQPage Schema
How do I analyze codebase architecture to find dependency cycles and coupling hotspots?

You can refactor complex codebases with tangled dependencies using a coordinated multi-agent workflow. This approach orchestrates analysis, planning, implementation, and validation steps to safely restructure modules while maintaining rollback awareness throughout the entire process.

What is the best way to plan a large-scale modular restructuring for a software system?

Multi-agent refactoring coordinates refactor, validation, and review steps across single, fan-out, or independent pipelines. This parallel implementation and verification approach reduces friction and ensures that structural changes are validated concurrently rather than sequentially.

How does multi-agent code review work for complex refactoring workflows?

Multi-agent code review orchestrates validation and review outputs across coordinated pipelines after refactoring. It verifies structural improvements against the baseline report, ensuring dependency cycles and coupling hotspots are resolved while maintaining safe rollback-aware execution throughout the verification process.

Can I use architecture analysis for a codebase with severe layering violations and dead code?

You need a codebase requiring structural improvement, such as one with tangled dependencies or risky module structure. The workflow then guides you from diagnosis through verified improvement using coordinated multi-agent teams.

When should I not use a multi-agent workflow for codebase refactoring?

Multi-agent refactoring is designed for complex software systems with tangled dependencies or risky module structures. You should avoid this approach for minor localized changes or simple codebases that do not require coordinated parallel implementation, baseline reporting, and rollback-aware validation pipelines.