TE

team-composition-patterns

Helps users size and configure agent teams for optimal performance across different complexity levels.

Install

mkdir -p .claude/skills/team-composition-patterns && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/5162" && unzip -o skill.zip -d .claude/skills/team-composition-patterns && rm skill.zip

Installs to .claude/skills/team-composition-patterns

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

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.
553 chars✓ has a “when” triggerlonger than Claude Code's old 250-char listing cap (fine on current versions)
Beginner

Key capabilities

  • Determine optimal team size based on task complexity
  • Select preset team configurations like Review or Debug Teams
  • Choose appropriate `subagent_type` for each role
  • Configure teammate display modes for different environments
  • Build custom team compositions for unique workflows
  • Coordinate agents using a `team-lead`

How it works

It provides heuristics for team sizing, defines preset team compositions with specific agent types, and guides the selection of `subagent_type` based on required tools. It also covers display mode configuration and custom team guidelines.

Inputs & outputs

You give it
Task complexity, desired team function, or specific agent roles
You get back
Recommended team size, agent types, and configuration settings

When to use team-composition-patterns

  • Sizing an agent team for a large feature
  • Choosing agent roles for a migration
  • Configuring agent display modes

About this skill

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

ComplexityTeam SizeWhen to Use
Simple1-2Single-dimension review, isolated bug, small feature
Moderate2-3Multi-file changes, 2-3 concerns, medium features
Complex3-4Cross-cutting concerns, large features, deep debugging
Very Complex4-5Full-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
  • Default dimensions: security, performance, architecture
  • Use when: Code changes need multi-dimensional quality assessment

Debug Team

  • Size: 3 investigators
  • Agents: 3x team-debugger
  • Default hypotheses: 3 competing hypotheses
  • Use when: Bug has multiple plausible root causes

Feature Team

  • Size: 3 (1 lead + 2 implementers)
  • Agents: 1x team-lead + 2x team-implementer
  • Use when: Feature can be decomposed into parallel work streams

Fullstack Team

  • Size: 4 (1 lead + 3 implementers)
  • Agents: 1x team-lead + 1x frontend team-implementer + 1x backend team-implementer + 1x test team-implementer
  • Use when: Feature spans frontend, backend, and test layers

Research Team

  • Size: 3 researchers
  • Agents: 3x general-purpose
  • Default areas: Each assigned a different research question, module, or topic
  • Capabilities: Codebase search (Grep, Glob, Read), web search (WebSearch, WebFetch)
  • Use when: Need to understand a codebase, research libraries, compare approaches, or gather information from code and web sources in parallel

Security Team

  • Size: 4 reviewers
  • Agents: 4x team-reviewer
  • Default dimensions: OWASP/vulnerabilities, auth/access control, dependencies/supply chain, secrets/configuration
  • Use when: Comprehensive security audit covering multiple attack surfaces

Migration Team

  • Size: 4 (1 lead + 2 implementers + 1 reviewer)
  • Agents: 1x team-lead + 2x team-implementer + 1x team-reviewer
  • Use when: Large codebase migration (framework upgrade, language port, API version bump) requiring parallel work with correctness verification

Agent Type Selection

When spawning teammates with the Agent tool, choose subagent_type based on what tools the teammate needs:

Agent TypeTools AvailableUse For
general-purposeAll tools (Read, Write, Edit, Bash, etc.)Implementation, debugging, any task requiring file changes
ExploreRead-only tools (Read, Grep, Glob)Research, code exploration, analysis
PlanRead-only toolsArchitecture planning, task decomposition
agent-teams:team-reviewerRead/search/Bash plus TaskList/TaskGet/TaskUpdate/SendMessageCode review with structured findings
agent-teams:team-debuggerRead/search/Bash plus TaskList/TaskGet/TaskUpdate/SendMessageHypothesis-driven investigation
agent-teams:team-implementerRead/Write/Edit/search/Bash plus TaskList/TaskGet/TaskUpdate/SendMessageBuilding features within file ownership boundaries
agent-teams:team-leadRead/search/Bash plus Agent Teams coordination toolsTeam orchestration and coordination

Key distinction: Read-only agents (Explore, Plan) cannot modify files. Never assign implementation tasks to read-only agents.

Display Mode Configuration

Configure in ~/.claude/settings.json:

{
  "teammateMode": "tmux"
}
ModeBehaviorBest For
"tmux"Each teammate in a tmux paneDevelopment workflows, monitoring multiple agents
"iterm2"Each teammate in an iTerm2 tabmacOS users who prefer iTerm2
"in-process"All teammates in same processSimple tasks, CI/CD environments

Custom Team Guidelines

When building custom teams:

  1. Every team needs a coordinator — Either designate a team-lead or have the user coordinate directly
  2. Match roles to agent types — Use specialized agents (reviewer, debugger, implementer) when available
  3. Avoid duplicate roles — Two agents doing the same thing wastes resources
  4. Define boundaries upfront — Each teammate needs clear ownership of files or responsibilities
  5. Keep it small — 2-4 teammates is the sweet spot; 5+ requires significant coordination overhead

Troubleshooting

A teammate was spawned as Explore but needs to write files. Explore and Plan are read-only agents. Change the subagent_type to general-purpose or an appropriate specialized agent type. Never assign implementation tasks to read-only agents.

The team is growing too large and coordination is slowing everything down. Each additional teammate adds communication overhead. Consolidate roles: can one agent cover two dimensions? A 4-person team doing 6 independent tasks is usually better served by 3 agents covering 2 tasks each.

tmux mode is not showing panes. Ensure tmux is installed and a session is already running before spawning teammates. The in-process mode works without tmux and is suitable for CI or scripted environments.

Two reviewers are flagging the same issues. The review dimensions overlap. Redefine each reviewer's focus area: one on correctness/logic, one on security, one on performance/scalability. Overlapping coverage wastes tokens and produces duplicate findings.

A team-lead is spawning teammates but they are not receiving tasks. Verify that the lead is using the Agent tool to spawn teammates and passing complete context in the prompt. Teammates start fresh with no prior conversation history — they need all relevant information in their initial prompt.

Related Skills

When not to use it

  • When assigning implementation tasks to read-only agents like `Explore` or `Plan`
  • When two agents are performing the same role, leading to duplicate work
  • When a team grows too large, causing significant coordination overhead

Limitations

  • Read-only agents (`Explore`, `Plan`) cannot modify files.
  • Each additional teammate adds communication overhead.
  • Teammates start fresh with no prior conversation history.

How it compares

This skill offers structured patterns and presets for agent team composition, providing a guided approach to team formation rather than ad-hoc agent spawning.

Compared to similar skills

team-composition-patterns side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
team-composition-patterns (this skill)12moNo flagsBeginner
trello412moReviewBeginner
executing-plans63moNo flagsIntermediate
github-project-management46moReviewAdvanced

Try saying

Example prompts that trigger this skill in your AI assistant.

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