swarm-swarm

name	swarm-swarm
description	Self-claiming pool orchestration. Workers race to claim tasks from a shared pool, loop until the pool is empty.

Swarm Orchestration (Self-Claiming Pool)

Overview

This skill is invoked by the swarm dispatcher. You should already have the goal, target, and selected roles from the dispatcher. If invoked directly, start from step 1.

Orchestrate a pool of interchangeable workers that self-assign from a shared task list. Workers claim tasks, complete them, and loop back for more until the pool is empty.

How This Differs from Fan-Out

• Fan-out: one specialist per role, each gets a unique task
• Swarm: interchangeable workers share a task pool. Workers loop (claim multiple tasks). Task pool can be larger than worker count.

When to Use

• Large workloads with many independent, similar-sized tasks
• Tasks that don't require specialized expertise per task
• The number of tasks exceeds the number of workers

When NOT to Use

• Tasks require different specialist expertise (use fan-out)
• Sequential dependencies between tasks (use pipeline)
• Tasks need structured merging (use map-reduce)

Checklist

You MUST complete these steps in order:

1. Identify goal and target
2. Read config and determine worker role/count
3. Decompose target into work units
4. Check for existing team
5. Confirm with user
6. Create team and tasks
7. Spawn workers
8. Collect findings
9. Synthesize and present report
10. Await user instructions
11. Shutdown and cleanup

Step 1: Identify Goal and Target

Determine from the user's request (or dispatcher context):

• Goal: What is being done? (e.g., "audit all modules", "review all API endpoints")
• Target: Which files, directories, or scope?

If unclear, ask the user. Do not guess scope.

Step 2: Read Config and Determine Workers

Read $CLAUDE_PLUGIN_ROOT/config/swarm-roles.yaml to get the preset config.

From the preset, determine:

• worker_role: the role all workers share (default: researcher)
• worker_count: how many concurrent workers to spawn (default: 3)

Validation

The dispatcher has already validated config shape (role existence, required fields, subagent_type values, numeric ranges). The checks below cover swarm-specific semantics.

• Scale warning: if worker_count > 7, warn the user that large swarms may hit context limits and recommend 3-5 workers.

Step 3: Decompose Target into Work Units

Analyze the target to determine discrete work units. Each work unit becomes one task in the pool:

• One task per module or directory
• One task per file group
• One task per endpoint or component

The number of tasks can (and often should) exceed the worker count. Workers will loop through the pool.

Step 4: Check for Existing Team

Only one team can exist per session. Before creating a new team, check if one already exists.

If a team exists:

• Active swarm: warn the user that a swarm is already running and offer to shut it down first (TeamDelete).
• Orphaned team (from a crashed session or /resume): agents from the previous session are gone but the team and task list persist. Offer the user two options:
  1. Delete and restart: TeamDelete the orphaned team, then proceed with a fresh swarm.
  2. Salvage completed work: check TaskList for completed tasks, synthesize any available findings from completed tasks, then TeamDelete and optionally re-run incomplete tasks.

Step 5: Confirm with User

Present the dispatch plan using AskUserQuestion:

I'll dispatch a swarm with these parameters:
- Worker role: {role name}
- Worker count: {N}
- Task pool: {M} tasks
- Target: {files/scope}

Tasks:
1. {work unit 1}
2. {work unit 2}
...

Proceed?

Do NOT spawn anything until the user confirms.

Step 6: Create Team and Tasks

Team Naming

Use format: swarm-swarm-{goal-slug}-{timestamp}

Generate the timestamp from the current date/time as a Unix epoch.

Create Team

TeamCreate with team_name: "swarm-swarm-{goal-slug}-{timestamp}"

Create Tasks

One task per work unit via TaskCreate:

• subject: imperative title for the work unit
• description: detailed scope, specific files/modules, reporting expectations
• activeForm: present-continuous spinner label

All tasks are independent — no blocks/blockedBy dependencies. No owner assigned — workers self-claim.

Step 7: Spawn Workers

Spawn N worker agents via Agent with:

• team_name: the team name from step 6
• name: worker-{n} (e.g., worker-1, worker-2)
• subagent_type: from the worker role config
• model: from the worker role config (if specified)
• run_in_background: true
• prompt: composed from the parts below

Isolation Handling

Before spawning, check the worker role's isolation field:

• If isolation: worktree is set:
  • Override subagent_type to general-purpose
  • Print a note: Role {name}: using general-purpose (worktree isolation requires write access)
  • Pass isolation: "worktree" to the Agent tool call
• If isolation is absent: use the role's subagent_type as-is

Prompt Construction

Part 1: Identity and Loop Instructions

Your name is {name}. You are part of team {team_name}.

You are a pool worker. Your workflow is a loop:

1. Check TaskList for unclaimed tasks (status: pending, no owner)
2. Claim one by setting yourself as owner and marking it in_progress
3. Verify the claim: call TaskGet on the task you claimed. If the
   owner is not your name, another worker claimed it first — go back
   to step 1
4. Complete the work described in the task
5. Send your findings to the team lead via SendMessage
   - Include a summary field (5-10 words)
   - Include the task subject in your message
6. Mark the task as completed
7. Go back to step 1

When no unclaimed tasks remain, go idle.

Part 2: Role Prompt

The prompt field from swarm-roles.yaml for the worker role.

Part 3: Goal and Target Context

## Goal

{goal description from user}

## Target

{target scope — workers will self-select from the task pool}

{any additional context the user provided}

Step 8: Collect Findings

Workers send findings via SendMessage after each task they complete. Messages are delivered automatically.

Normal flow: Workers loop through multiple tasks, sending findings after each. Workers go idle when the pool is empty.

Error handling:

• Idle worker without findings: send a message asking for status
• No response after nudge: note in report, mark tasks as blocked
• Stuck tasks: reassign by removing the owner if a worker stalls

Step 9: Synthesize and Present Report

Once all tasks are completed (or you've noted stuck ones):

Synthesize findings into a unified report organized by theme or severity, not by worker or task.

Report Structure

## Swarm Analysis Report

**Goal:** {goal}
**Target:** {target}
**Workers:** {N workers, M tasks completed}

### Critical Issues
{findings rated critical/high, with file:line references}

### Important Issues
{findings rated medium/important}

### Suggestions
{lower-priority findings and recommendations}

### Summary
{brief overall assessment — 2-3 sentences}

Step 10: Await User Instructions

After presenting the report:

• Do NOT fix issues workers found
• Do NOT shut down the team automatically
• Do NOT proceed past reporting without user input

Wait for the user to decide next steps.

Step 11: Shutdown and Cleanup

When the user indicates they're done:

1. Send shutdown_request to each worker via SendMessage (include the monitor agent if watchdog: true was active)
2. Wait for shutdown_response from each. If an agent does not respond after a reasonable wait, send one nudge message. If still unresponsive, proceed — the agent may have crashed or terminated.
3. Call TeamDelete to clean up. TeamDelete is the authoritative cleanup mechanism — it will fail if active agents remain. If it fails, retry after unresponsive agents have timed out.

Design Constraints

• Interchangeable workers: all workers use the same role prompt
• Self-claiming: workers find and claim their own tasks
• No dependencies: all tasks in the pool are independent
• One team per session: check before creating
• Lead synthesizes: present a unified report, not raw worker output
• User controls lifecycle: never auto-shutdown