orchestrating-swarms

everyinc/compound-engineering-plugin · updated Apr 8, 2026

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$npx skills add https://github.com/everyinc/compound-engineering-plugin --skill orchestrating-swarms
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summary

Master multi-agent orchestration using Claude Code's TeammateTool and Task system.

skill.md

Claude Code Swarm Orchestration

Master multi-agent orchestration using Claude Code's TeammateTool and Task system.


Primitives

Primitive What It Is File Location
Agent A Claude instance that can use tools. You are an agent. Subagents are agents you spawn. N/A (process)
Team A named group of agents working together. One leader, multiple teammates. ~/.claude/teams/{name}/config.json
Teammate An agent that joined a team. Has a name, color, inbox. Spawned via Task with team_name + name. Listed in team config
Leader The agent that created the team. Receives teammate messages, approves plans/shutdowns. First member in config
Task A work item with subject, description, status, owner, and dependencies. ~/.claude/tasks/{team}/N.json
Inbox JSON file where an agent receives messages from teammates. ~/.claude/teams/{name}/inboxes/{agent}.json
Message A JSON object sent between agents. Can be text or structured (shutdown_request, idle_notification, etc). Stored in inbox files
Backend How teammates run. Auto-detected: in-process (same Node.js, invisible), tmux (separate panes, visible), iterm2 (split panes in iTerm2). See Spawn Backends. Auto-detected based on environment

How They Connect

flowchart TB
    subgraph TEAM[TEAM]
        Leader[Leader - you]
        T1[Teammate 1]
        T2[Teammate 2]

        Leader <-->|messages via inbox| T1
        Leader <-->|messages via inbox| T2
        T1 <-.->|can message| T2
    end

    subgraph TASKS[TASK LIST]
        Task1["#1 completed: Research<br/>owner: teammate1"]
        Task2["#2 in_progress: Implement<br/>owner: teammate2"]
        Task3["#3 pending: Test<br/>blocked by #2"]
    end

    T1 --> Task1
    T2 --> Task2
    Task2 -.->|unblocks| Task3

Lifecycle

flowchart LR
    A[1. Create Team] --> B[2. Create Tasks]
    B --> C[3. Spawn Teammates]
    C --> D[4. Work]
    D --> E[5. Coordinate]
    E --> F[6. Shutdown]
    F --> G[7. Cleanup]

Message Flow

sequenceDiagram
    participant L as Leader
    participant T1 as Teammate 1
    participant T2 as Teammate 2
    participant Tasks as Task List

    L->>Tasks: TaskCreate (3 tasks)
    L->>T1: spawn with prompt
    L->>T2: spawn with prompt

    T1->>Tasks: claim task #1
    T2->>Tasks: claim task #2

    T1->>Tasks: complete #1
    T1->>L: send findings (inbox)

    Note over Tasks: #3 auto-unblocks

    T2->>Tasks: complete #2
    T2->>L: send findings (inbox)

    L->>T1: requestShutdown
    T1->>L: approveShutdown
    L->>T2: requestShutdown
    T2->>L: approveShutdown

    L->>L: cleanup

Table of Contents

  1. Core Architecture
  2. Two Ways to Spawn Agents
  3. Built-in Agent Types
  4. Plugin Agent Types
  5. TeammateTool Operations
  6. Task System Integration
  7. Message Formats
  8. Orchestration Patterns
  9. Environment Variables
  10. Spawn Backends
  11. Error Handling
  12. Complete Workflows

Core Architecture

How Swarms Work

A swarm consists of:

  • Leader (you) - Creates team, spawns workers, coordinates work
  • Teammates (spawned agents) - Execute tasks, report back
  • Task List - Shared work queue with dependencies
  • Inboxes - JSON files for inter-agent messaging

File Structure

~/.claude/teams/{team-name}/
├── config.json              # Team metadata and member list
└── inboxes/
    ├── team-lead.json       # Leader's inbox
    ├── worker-1.json        # Worker 1's inbox
    └── worker-2.json        # Worker 2's inbox

~/.claude/tasks/{team-name}/
├── 1.json                   # Task #1
├── 2.json                   # Task #2
└── 3.json                   # Task #3

Team Config Structure

{
  "name": "my-project",
  "description": "Working on feature X",
  "leadAgentId": "team-lead@my-project",
  "createdAt": 1706000000000,
  "members": [
    {
      "agentId": "team-lead@my-project",
      "name": "team-lead",
      "agentType": "team-lead",
      "color": "#4A90D9",
      "joinedAt": 1706000000000,
      "backendType": "in-process"
    },
    {
      "agentId": "worker-1@my-project",
      "name": "worker-1",
      "agentType": "Explore",
      "model": "haiku",
      "prompt": "Analyze the codebase structure...",
      "color": "#D94A4A",
      "planModeRequired": false,
      "joinedAt": 1706000001000,
      "tmuxPaneId": "in-process",
      "cwd": "/Users/me/project",
      "backendType": "in-process"
    }
  ]
}

Two Ways to Spawn Agents

Method 1: Task Tool (Subagents)

Use Task for short-lived, focused work that returns a result:

Task({
  subagent_type: "Explore",
  description: "Find auth files",
  prompt: "Find all authentication-related files in this codebase",
  model: "haiku"  // Optional: haiku, sonnet, opus
})

Characteristics:

  • Runs synchronously (blocks until complete) or async with run_in_background: true
  • Returns result directly to you
  • No team membership required
  • Best for: searches, analysis, focused research

Method 2: Task Tool + team_name + name (Teammates)

Use Task with team_name and name to spawn persistent teammates:

// First create a team
Teammate({ operation: "spawnTeam", team_name: "my-project" })

// Then spawn a teammate into that team
Task({
  team_name: "my-project",        // Required: which team to join
  name: "security-reviewer",      // Required: teammate's name
  subagent_type: "security-sentinel",
  prompt: "Review all authentication code for vulnerabilities. Send findings to team-lead via Teammate write.",
  run_in_background: true         // Teammates usually run in background
})

Characteristics:

  • Joins team, appears in config.json
  • Communicates via inbox messages
  • Can claim tasks from shared task list
  • Persists until shutdown
  • Best for: parallel work, ongoing collaboration, pipeline stages

Key Difference

Aspect Task (subagent) Task + team_name + name (teammate)
Lifespan Until task complete Until shutdown requested
Communication Return value Inbox messages
Task access None Shared task list
Team membership No Yes
Coordination One-off Ongoing

Built-in Agent Types

These are always available without plugins:

Bash

Task({
  subagent_type: "Bash",
  description: "Run git commands",
  prompt: "Check git status and show recent commits"
})
  • Tools: Bash only
  • Model: Inherits from parent
  • Best for: Git operations, command execution, system tasks

Explore

Task({
  subagent_type: "Explore",
  description: "Find API endpoints",
  prompt: "Find all API endpoints in this codebase. Be very thorough.",
  model: "haiku"  // Fast and cheap
how to use orchestrating-swarms

How to use orchestrating-swarms on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add orchestrating-swarms
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/everyinc/compound-engineering-plugin --skill orchestrating-swarms

The skills CLI fetches orchestrating-swarms from GitHub repository everyinc/compound-engineering-plugin and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/orchestrating-swarms

Reload or restart Cursor to activate orchestrating-swarms. Access the skill through slash commands (e.g., /orchestrating-swarms) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.558 reviews
  • Advait Tandon· Dec 28, 2024

    Registry listing for orchestrating-swarms matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Maya Thompson· Dec 24, 2024

    orchestrating-swarms has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Diego Chawla· Dec 20, 2024

    Useful defaults in orchestrating-swarms — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Mei Desai· Dec 8, 2024

    Solid pick for teams standardizing on skills: orchestrating-swarms is focused, and the summary matches what you get after install.

  • Sophia Rahman· Dec 8, 2024

    We added orchestrating-swarms from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Kiara Jackson· Nov 27, 2024

    orchestrating-swarms has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • William Mehta· Nov 27, 2024

    orchestrating-swarms reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Omar Menon· Nov 15, 2024

    Solid pick for teams standardizing on skills: orchestrating-swarms is focused, and the summary matches what you get after install.

  • Kaira Jackson· Nov 3, 2024

    Registry listing for orchestrating-swarms matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Kaira Thompson· Oct 22, 2024

    Useful defaults in orchestrating-swarms — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

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