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Coordinate architect, builder, and reviewer agents for better coding.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "three-man-team" yet — see the docs or source repo.
Please split this requirement across three AI roles: Architect designs the solution and interfaces, Builder implements the code, and Reviewer performs code review and flags risks. Include each role’s responsibilities, execution order, and final conclusion.
A role-based plan, implementation guidance, and review conclusions.
Help me refactor this code using three roles: Architect analyzes current architecture issues, Builder proposes and applies the refactor, and Reviewer checks for regression risks.
A refactor path, code change suggestions, and regression checkpoints.
Simulate a three-person team handling this bug: Architect defines the problem scope, Builder writes the fix, and Reviewer verifies completeness and adds test suggestions.
A fix plan, patch approach, and test recommendations.
Solo developers can split a task into planning, implementation, and review to reduce back-and-forth edits. It suits people who want faster output with a structured workflow.
When you worry about omissions, edge cases, or regression risk, let the Reviewer inspect the Builder’s work separately. This helps catch issues earlier.
If you use Claude Code, VS Code, or Cursor and your AI supports context files, this skill fits into that development workflow.
It is a structured three-agent AI development team with Architect, Builder, and Reviewer collaborating on coding tasks. It emphasizes clear role separation and is optimized from production use.
The description says it works with Claude Code, VS Code, Cursor, and any AI that supports context files.
It splits the workflow into architecture, implementation, and review, making code output and risk checks more structured. Compared with a single assistant, it emphasizes role-based collaboration.
Plan multi-agent architectures, agent roles, and code collaboration strategies.
Run multi-agent teams to execute complex work from high-level instructions.
Coordinate specialized AI agents for software development, review, testing, and task tracking.
Review code or branches for correctness, compatibility, architecture, tests, performance, and security.
Query live architecture models, fetch target patterns, and check files for compliance.
Standardize planning, memory, verification, and review across AI coding agents.