team-composition-patterns

Designs optimal multi-agent team configurations for Claude Code tasks.

Updated Apr 7, 2026
One-click install
npx skills add https://github.com/dxas90/opsy-bag --skill team-composition-patterns-dxas90
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: team-composition-patterns
Source: https://github.com/dxas90/opsy-bag/tree/main/.claude/teams/musketeers/skills/team-composition-patterns
Command: npx skills add https://github.com/dxas90/opsy-bag --skill team-composition-patterns-dxas90

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you decide how many agents to spawn, which agent types to use, and how to configure their display modes when building multi‑agent teams for Claude Code projects, eliminating guesswork and coordination overhead.

Core Features & Use Cases

  • Team Sizing Heuristics: Choose the right number of teammates based on task complexity (simple to very complex).
  • Preset Team Configurations: Ready‑made definitions for review, debug, feature, full‑stack, security, migration, and more.
  • Agent Type Selection Guide: Map responsibilities to specialized sub‑agent types (Athos, Porthos, Aramis, Dumas, DArtagnan, etc.).
  • Display Mode Configuration: Quickly set tmux, iTerm2, or in‑process modes for local or CI environments.
  • Custom Team Guidelines & Troubleshooting: Best‑practice rules for building bespoke teams and handling common issues.

Quick Start

Ask the team-composition-patterns skill to suggest a suitable team setup for a complex feature implementation.

Frequently Asked Questions about team-composition-patterns

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

FAQPage Schema
How do I determine the right number of agents for a multi-agent Claude Code task?

Team sizing requires evaluating task complexity from simple to very complex. This skill applies specific heuristics to recommend the optimal agent count, ensuring coordination efficiency and eliminating the guesswork involved in manual team sizing.

What are the best preset team configurations for code review and security audits?

Preset team configurations provide ready-made definitions for code review, security audits, debugging, and feature development. These presets map specific multi-agent responsibilities to specialized sub-agent types, allowing immediate deployment without manual role assignment.

How do I select the correct agent types for specialized roles in a feature development team?

Agent type selection relies on mapping task responsibilities to specialized sub-agent types like Athos, Porthos, Aramis, Dumas, and DArtagnan. This skill provides guidelines to match agent capabilities with your specific feature development requirements.

How do I configure display modes for local or CI environments when spawning agents?

Display mode configuration involves selecting tmux, iTerm2, or in-process modes based on your execution environment. This skill provides rules to quickly set the correct display mode for both local development and CI pipelines.

Can I build custom multi-agent teams or should I only use preset configurations?

You can build bespoke multi-agent teams using custom team guidelines and best-practice troubleshooting rules. The skill supports both ready-made presets for common tasks and flexible guidelines for creating custom agent setups.

Why is my multi-agent team experiencing coordination overhead during complex migrations?

Coordination overhead often stems from incorrect team sizing or mismatched agent types. This skill provides troubleshooting guidelines to resolve common multi-agent coordination issues and optimize configurations for complex migration tasks.