choosing-swarm-patterns

Overview

The Agent Relay workflow engine (@relayflows/core) supports 24 swarm patterns via a single swarm.pattern field. Patterns are configured declaratively in YAML or programmatically via the workflow() fluent builder — there are no standalone fanOut(...) / hubAndSpoke(...) helpers. Pick the simplest pattern that solves the problem; add complexity only when the system proves it's insufficient.

Two ways to run a pattern

1. YAML (portable):

import { runWorkflow } from '@relayflows/core';

const run = await runWorkflow('workflows/feature-dev.yaml', {
  vars: { task: 'Add OAuth login' },
});

2. Fluent builder (programmatic):

import { workflow } from '@relayflows/core';

const run = await workflow('feature-dev')
  .pattern('hub-spoke')
  .channel('swarm-feature-dev')
  .agent('lead', { cli: 'claude', role: 'lead' })
  .agent('developer', { cli: 'codex', role: 'worker', interactive: false })
  .step('plan', { agent: 'lead', task: 'Plan {{task}}' })
  .step('implement', { agent: 'developer', task: 'Implement: {{steps.plan.output}}', dependsOn: ['plan'] })
  .run();

Both paths hit the same WorkflowRunner.

Quick Decision Framework

Is the task independent per agent?
  YES → fan-out (parallel workers, hub collects)

Does each step need the previous step's output?
  YES → Is it strictly linear?
    YES → pipeline
    NO  → dag (parallel where possible, `dependsOn` edges)

Does a coordinator need to stay alive and adapt?
  YES → hub-spoke (single-level hub + workers)
        hierarchical (structurally identical in current impl; use for naming/intent)

Is the task about making a decision?
  YES → Do agents need to argue opposing sides?
    YES → debate (adversarial, full mesh)
    NO  → consensus (cooperative, full mesh + coordination.consensusStrategy)

Does the right specialist emerge during processing?
  YES → handoff (sequential chain, one active at a time)

Do all agents need to freely collaborate?
  YES → mesh (full peer-to-peer edges)

Is cost the primary concern?
  YES → cascade (chain of increasingly capable agents; each step's prompt
        decides whether to pass through or redo the prior output)