Agent skill · Security

team-composition-patterns

Design optimal agent team compositions with sizing heuristics, preset configurations, and agent type selection. Use this skill when deciding how many agents to spawn for a task, when choosing between a review team versus a feature team versus a debug team, when selecting the correct subagent_type for each role to ensure agents have the tools they need, when configuring display modes (tmux, iTerm2, in-process) for a CI or local environment, or when building a custom team composition for a non-standard workflow such as a migration or security audit.

Seth Hobson38,331★ · +219/wk · 1 repos on radarProfile →
claude-codecodexcopilotcursorMIT
Install
npx skills add wshobson/agents --skill team-composition-patterns --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 3
SKILL.md size: 8 KB
Bundled scripts: none
Version: 1.0.2
Path: plugins/agent-teams/skills/team-composition-patterns/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 38,479 · +148 this week
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Team Composition Patterns Best practices for composing multi-agent teams, selecting team sizes, choosing agent types, and configuring display modes for Claude Code's Agent Teams feature. ## When to Use This Skill - Deciding how many teammates to spawn for a task - Choosing between preset team configurations - Selecting the right agent type (subagent_type) for each role - Configuring teammate display modes (tmux, iTerm2, in-process) - Building custom team compositions for non-standard workflows ## Team Sizing Heuristics | Complexity | Team Size | When to Use | | ------------ | --------- | ----------------------------------------------------------- | | Simple | 1-2 | Single-dimension review, isolated bug, small feature | | Moderate | 2-3 | Multi-file changes, 2-3 concerns, medium features | | Complex | 3-4 | Cross-cutting concerns, large features, deep debugging | | Very Complex | 4-5 | Full-stack features, comprehensive reviews, systemic issues | **Rule of thumb**: Start with the smallest team that covers all required dimensions. Adding teammates increases coordination overhead. ## Preset Team Compositions ### Review Team - **Size**: 3 reviewers - **Agents**: 3x `team-reviewer` -

What's inside
Steps it walks through
  1. When to Use This Skill
  2. Team Sizing Heuristics
  3. Preset Team Compositions
  4. Review Team
  5. Debug Team
  6. Feature Team
  7. Fullstack Team
  8. Research Team
  9. Security Team
  10. Migration Team
  11. Agent Type Selection
  12. Display Mode Configuration
  13. Custom Team Guidelines
  14. Troubleshooting
Ships with 2 files
  • references/agent-type-selection.md
  • references/preset-teams.md
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About this skill
What does the team-composition-patterns skill do?

Design optimal agent team compositions with sizing heuristics, preset configurations, and agent type selection. Use this skill when deciding how many agents to spawn for a task, when choosing between a review team versus a feature team versus a debug team, when selecting the correct subagent_type for each role to ensure agents have the tools they need, when configuring display modes (tmux, iTerm2, in-process) for a CI or local environment, or when building a custom team composition for a non-standard workflow such as a migration or security audit.

How do I install it?

Run `npx skills add wshobson/agents --skill team-composition-patterns --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From wshobson/agents, a repository with 38,479 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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