matthew-a-gordon

Claude Code Agent Teams

AI Agentv1.0.0
By matthew-a-gordonUpdated 2026-05-11claude-code-teams@clawhub_matthew-a-gordon/claude-code-teams
Task AutomationMulti-Agent CollaborationWorkflow Orchestration#Debugging

According to AlphaMoat, as of 2026-09, Claude Code Agent Teams has 2,543 downloads and 3 stars — ranked #4,063 of 5,078 AI skills overall, and #822 of 969 in AI Agent.

Installs
105
Downloads
2.5K
Stars
3
Overall Rank
#4,063
Top 81% overall · Top 85% in AI Agent
PlatformInstallsDownloadsStarsComments
ClawHub ↗742.5K2-
SkillHub ↗1052.5K3—

Platforms count differently and update at different times.

What this skill does

The source recommends clear task boundaries, roles, and integration steps, while weighing coordination costs. The supporting card warns that force cleanup may terminate unrelated PTY sessions and lose in-progress work; inspect cleanup scripts and prefer graceful shutdown.

Profile published 2026-10-29

What you can do with it

  • Split independent investigation or implementation work.
  • Set clear tasks, file boundaries, and expected outputs for teammates.
  • Plan progress monitoring and safe cleanup.

When to use it

  • When multiple tasks can proceed independently without shared-state dependencies.
  • When parallel perspectives help with cross-domain reviews or competing hypotheses.
  • Before cleanup, when avoiding termination of unrelated sessions or loss of work matters.

Example prompts

Generated from the skill’s documentation as examples; not results of actual runs.

Decide whether these work items fit parallel Claude Code teams.
Draft roles, file boundaries, and integration steps for a parallel code review.

Monthly Trend

Downloads2.5K
1.1K1.9K2.7K2026-03 · Downloads 1.2K2026-05 · Downloads 1.8K2026-06 · Downloads 2.0K2026-07 · Downloads 2.2K2026-08 · Downloads 2.4K2026-09 · Downloads 2.5K26-0326-09
Stars3
2332026-03 · Stars 22026-05 · Stars 32026-06 · Stars 32026-07 · Stars 32026-08 · Stars 32026-09 · Stars 326-0326-09

The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.

MonthDownloadsMoMStars
2026-092.5K—3
2026-082.4K+6.6%3
2026-072.2K+13.9%3
2026-062.0K+9.5%3
2026-051.8K—3
2026-031.2K—2

SKILL.md (original)

The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.

5.5 KB · ClawHub v1.0.0
---
name: claude-code-teams
description: Production skill for orchestrating Claude Code's native agent teams feature. Use when: (1) Multi-lens reviews, (2) Competing hypotheses debugging, (3) Full-stack features, (4) Architecture debates, (5) Cross-domain investigations.
metadata:
  openclaw:
    emoji: "🎭"
    requires:
      bins: ["claude"]
      env: ["CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS"]
    version: "1.0.0"
Show all (173 lines)
    author: "Matthew Gordon"
    tags: ["agents", "teams", "claude-code", "orchestration", "coordination"]
---

# Claude Code Agent Teams

Orchestrate multiple Claude Code agents working together on complex tasks. Agents coordinate through a shared task list, message each other directly, and work in parallel on independent scopes.

## When to Use

✅ **Use for parallel independent work:**
- Multi-lens code reviews (security, performance, tests in parallel)
- Debugging with competing hypotheses (test theories simultaneously)
- Full-stack features (frontend/backend/tests by separate specialists)
- Architecture decisions (adversarial debate produces stronger ADRs)
- Cross-domain investigations (bottleneck analysis across systems)
- Data-parallel work (inventory classification, bulk refactoring)

❌ **Don't use for:**
- Sequential work with tight dependencies
- Same-file edits (conflict risk)
- Simple tasks (coordination overhead > benefit)
- Learning/exploration (single agent with full context is better)

**Rule of thumb:** Teams multiply token cost 3-4x. Use only when parallelization benefit exceeds coordination overhead.

## Quick Start

### 1. Enable Feature

**Environment variable:**
```bash
export CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1
```

**Or settings file** (`~/.claude/settings.json`):
```json
{
  "env": {
    "CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS": "1"
  }
}
```

### 2. Validate Setup

```bash
./scripts/validate-setup.sh
```

Checks for: env var set, `claude` CLI available, `tmux` installed (optional).

### 3. Pick Template

| Template | Use Case |
|----------|----------|
| `parallel-review.md` | Multi-lens code review (security + performance + tests) |
| `competing-hypotheses.md` | Debug by testing competing theories |
| `fullstack-feature.md` | Frontend/backend/tests coordination |
| `architecture-decision.md` | ADR with adversarial debate |
| `bottleneck-analysis.md` | Cross-domain performance investigation |
| `inventory-classification.md` | Data-parallel classification/refactoring |

Each template includes: when to use, team structure, copy-paste spawn prompt, expected outcomes.

### 4. Spawn Team

```bash
claude --pty
# Paste spawn prompt from template
```

Monitor with `./scripts/team-monitor.sh` (separate terminal) or `Ctrl+T` (in Claude Code).

## Core Principles

1. **Clear file boundaries** - Each teammate owns different files/directories (prevents conflicts)
2. **Use delegate mode** - Lead coordinates, teammates implement (include in spawn prompt)
3. **Size tasks appropriately** - 5-6 self-contained tasks per teammate
4. **Wait for completion** - Don't let lead merge results while teammates are mid-task
5. **Start with research** - Spawn researchers before builders to establish shared understanding

## Cost Management

Agent teams multiply token usage **3-4x** vs single session. Each teammate has its own context window.

**Optimize with:**
- **Model mixing** - Opus for lead (strategic), Sonnet for teammates (tactical) = ~40% savings
- **Minimize broadcasts** - Direct messages only (broadcasts copy to all teammates)
- **Right-size teams** - 3 teammates usually optimal; 6+ only for highly parallel work

See `references/cost-management.md` for detailed strategies.

## Troubleshooting

**Teammates not spawning?**
- Verify `CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1` is set
- Restart Claude Code after setting env var

**File conflicts?**
- Define explicit file boundaries in spawn prompt (directory-level ownership)

**Lead implementing instead of coordinating?**
- Add "Use delegate mode: coordinate but don't implement" to spawn prompt
- Or press Shift+Tab to cycle into delegate mode

See `references/troubleshooting.md` for full list.

## Automation

**Monitor progress:**
```bash
./scripts/team-monitor.sh
```

**Cleanup (graceful shutdown):**
```bash
./scripts/team-cleanup.sh
```

## Display Modes

**In-process** (default) - All teammates in main terminal
- `Shift+Up/Down` - Select teammate
- `Ctrl+T` - Toggle task list
- `Escape` - Interrupt teammate

**Split-pane** (requires tmux or iTerm2) - Each teammate gets own pane
- Set `teammateMode: "tmux"` in `~/.claude/settings.json`

## References

- **`templates/`** - 6 copy-paste ready spawn prompts with usage guidance
- **`scripts/`** - Automation helpers (validate, monitor, cleanup)
- **`references/best-practices.md`** - When to use teams, task sizing, file boundaries
- **`references/cost-management.md`** - Token optimization strategies
- **`references/troubleshooting.md`** - Common issues and solutions
- **`examples/`** - Real-world walkthroughs (PR review, bug hunt, feature build)

## Comparison

| Approach | Best For |
|----------|----------|
| Single session | Sequential work, exploration |
| Agent teams (this skill) | Parallel independent tasks with coordination |
| OpenClaw subagents | Background work, long-running tasks |

## Contributing

Found a useful pattern? Submit PR with:
1. Template or example
2. When to use + team structure
3. Spawn prompt + expected outcomes

## Credits

Built with insights from Claude Code documentation, ClaudeFast patterns, and OpenClaw community.

---

**Repository:** https://github.com/matthew-a-gordon/claude-code-teams  
**License:** MIT

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Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.