Claude-code-customes team-builder

Intelligently compose and deploy Claude Code Agent Teams based on user requirements. Auto-selects optimal team composition from all available skills and agents (project, user, global, plugin scopes), generates task dependency graphs, and orchestrates team lifecycle. Use when creating multi-agent teams for complex tasks requiring parallel specialized work.

install
source · Clone the upstream repo
git clone https://github.com/sc30gsw/claude-code-customes
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/sc30gsw/claude-code-customes "$T" && mkdir -p ~/.claude/skills && cp -r "$T/.claude/skills/team-builder" ~/.claude/skills/sc30gsw-claude-code-customes-team-builder && rm -rf "$T"
manifest: .claude/skills/team-builder/SKILL.md
source content

Team Builder

Automated Agent Team composition and deployment. Analyzes user requirements to propose optimal team structure, with teammates leveraging all available skills and agents across every scope.

Overview

This skill automates the process of creating Claude Code Agent Teams by:

  • Analyzing user requirements to recommend optimal team composition
  • Discovering all available skills/agents across 5 scopes (project, user, global, plugin marketplaces, plugin cache)
  • Generating task dependency graphs with parallel/sequential flows
  • Injecting relevant skills into teammate spawn prompts
  • Supporting auto, template, and manual composition modes

Args

ArgShortDescriptionExample
--agents
-a
Agent types to include (comma-separated)
-a "planner,system-architect"
--skills
-s
Skills for teammates to use (comma-separated)
-s "tdd-workflow,security-review"
--template
-t
Use predefined team template
-t feature-dev
--name
-n
Team name (auto-generated if omitted)
-n "auth-team"
--model
-m
Model strategy: deep/adaptive/fast/budget
-m adaptive
--size
Team size limit (default: auto, max: 5)
--size 3
--lead
-l
Lead agent type
-l planner
--dry-run
Preview composition without deploying
--dry-run
--auto
Auto-deploy without confirmation
--auto
--delegate
-d
Lead focuses on coordination only
--delegate
--plan-approval
-p
Require plan approval from teammates
-p
--display
Display mode: in-process or split
--display split

Workflow

AUTO Mode (default)

When no

--template
or
--agents
specified:

  1. Analyze Request: Detect domain keywords to identify the type of work
  2. Discover Resources: Run
    python scripts/discover_resources.py --format json
    to catalog all available agents and skills across all scopes
  3. Score Relevance: Match agents/skills to detected domain using the Domain Detection table below
  4. Propose Team: Generate optimal team composition with task dependencies
  5. Confirm: Present composition for user approval (skip with
    --auto
    )
  6. Deploy: Execute TeamCreate -> TaskCreate (with blockedBy) -> Task spawn (with team_name) for each member

TEMPLATE Mode (
-t
specified)

  1. Load Template: Read matching template from
    references/team-templates.md
  2. Customize Tasks: Inject user's request into task descriptions
  3. Override: Apply
    -a
    ,
    -s
    overrides if provided
  4. Deploy: Execute team deployment sequence

MANUAL Mode (
-a
only)

  1. Build Team: Create team from specified agent types
  2. Route Skills: Match
    -s
    skills to appropriate roles
  3. Generate Tasks: Auto-create tasks from user request
  4. Deploy: Execute team deployment sequence

Available Templates

TemplateUse CaseMembers
feature-dev
Full-cycle feature developmentplanner + architect + tester
investigation
Bug investigation and RCAanalyst + tester + researcher
refactor
Code quality improvementrefactorer + reviewer + tester
security-audit
Security assessmentsecurity + reviewer + tester
frontend
Frontend feature developmentdesigner + reviewer + e2e
full-stack
End-to-end developmentbackend + frontend + tester + security
documentation
Documentation creationwriter + analyst
exploration
Multi-perspective analysisux-analyst + tech-architect + devils-advocate

See

references/team-templates.md
for full template definitions with task flows and spawn prompts.

Domain Detection

DomainKeywordsRecommended AgentsRecommended Skills
Feature Devbuild, implement, create, add, featureplanner, system-architect, testing-specialist/plan, /tdd-workflow, /code-reviewer
Bug Investigationdebug, fix, investigate, error, bugroot-cause-analyst, testing-specialist/debug-error, /test-coverage
Refactoringrefactor, clean, improve, optimizerefactoring-expert, quality-engineer/refactor-clean, /code-reviewer
Securitysecurity, audit, vulnerability, authsecurity-reviewer, quality-engineer/security-review
FrontendUI, component, design, responsive, formfrontend-architect, e2e-runner/senior-frontend, /e2e, /ui-advice
BackendAPI, endpoint, database, server, servicesystem-architect, testing-specialist/senior-backend, /tdd-workflow
Documentationdocument, docs, spec, requirements, readmetechnical-writer, requirements-analyst/doc-engineer, /update-docs
Performanceperformance, optimize, slow, benchmark, latencyperformance-engineer, system-architect/test-coverage
Explorationexplore, research, analyze, evaluate, comparegeneral-purpose (multiple)/plan, /smart-think

Skill Injection

Embed in each teammate's spawn prompt to make skills discoverable:

You are the {role-name} on team "{team-name}". Your task is: {task-description}

## Available Skills
Invoke the following skills as needed during your work:
- /tdd-workflow: Test-driven development with 80%+ coverage
- /security-review: Comprehensive security checklist
- /code-reviewer: Code quality review
- /{plugin-skill}: {description from catalog}

## On Completion
1. Use TaskUpdate to mark your task as completed
2. Send a summary of your findings to team-lead via SendMessage

Skills listed are dynamically populated from

discover_resources.py
output, matching the teammate's role to relevant skills from ALL scopes.

Model Selection Strategy

Strategy (
-m
)
LeadArchitect/AnalystWorker
deep
opusopusopus
adaptive
(default)
opusopussonnet
fast
sonnetsonnetsonnet
budget
sonnethaikuhaiku

Deployment Sequence

1. TeamCreate(team_name, description)
2. For each member:
   a. TaskCreate(subject, description, activeForm)
3. Set dependencies:
   a. TaskUpdate(taskId, addBlockedBy: [...])
4. For each member:
   a. Task(subagent_type, team_name, name, prompt, model, mode)
5. Assign initial tasks:
   a. TaskUpdate(taskId, owner: member-name, status: "in_progress")

When

--plan-approval
is set, spawn teammates with
mode: "plan"
so they submit plans for approval before implementing.

When

--delegate
is set, the lead agent focuses solely on coordination, task assignment, and synthesis.

Usage Examples

# Auto: compose from request analysis
/team-builder "Design and implement JWT authentication system"

# Template: use predefined template
/team-builder -t feature-dev "User management API"

# Manual: specify agents and skills
/team-builder -a "planner,frontend-architect,e2e-runner" -s "senior-frontend,e2e,ai-sdk"

# Dry-run: preview composition
/team-builder --dry-run "Large-scale refactoring"

# Budget + auto: cost-optimized auto-deploy
/team-builder -m budget --auto "Documentation cleanup"

# With plan approval for high-risk work
/team-builder -t full-stack -p "Payment processing system"

# Delegate mode: lead coordinates only
/team-builder -d -t feature-dev "New notification system"

# Split display for real-time monitoring
/team-builder --display split -t exploration "Evaluate microservices migration"

Resources

scripts/

  • discover_resources.py
    : Discovers all available agents and skills across all 5 scopes. Run with
    --format json|table
    and
    --scope project|user|global|plugin|all
    .

references/

  • team-templates.md
    : 8 predefined team templates with member definitions, task flows, and spawn prompt templates.
  • composition-guide.md
    : Team composition best practices including sizing, model selection, task granularity, file conflict avoidance, and anti-patterns.