
Choosing Swarm Patterns
- 1 installs
- Updated August 4, 2026
- agentworkforce/workflows
choosing-swarm-patterns is a Claude Code skill that provides a decision framework for selecting among Agent Relay's 24 multi-agent orchestration patterns.
About
This skill helps pick the right orchestration pattern when coordinating multiple AI agents with the Agent Relay SDK. It documents 24 swarm patterns configured through a single swarm.pattern field, with a decision framework and YAML plus fluent-builder examples. A developer uses it before writing a multi-agent workflow to choose the topology that fits the coordination problem.
- Decision framework for picking one of 24 Agent Relay swarm patterns
- Covers the core 10: fan-out, pipeline, hub-spoke, consensus, mesh, handoff, cascade, dag, debate, hierarchical
- Shows both YAML and fluent-builder configuration
Choosing Swarm Patterns by the numbers
- 1 all-time installs (skills.sh)
- Ranked #14,102 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
choosing-swarm-patterns capabilities & compatibility
- Capabilities
- agent orchestration · pattern selection · workflow design
- Use cases
- orchestration
npx skills add https://github.com/agentworkforce/workflows --skill choosing-swarm-patternsAdd your badge
Show developers this skill is listed on Skillselion. Paste this into your README.
| Installs | 1 |
|---|---|
| Last updated | August 4, 2026 |
| Repository | agentworkforce/workflows ↗ |
What it does
Choose the correct Agent Relay swarm pattern (fan-out, pipeline, hub-spoke, etc.) for a multi-agent coordination problem.
Who is it for?
Developers deciding which Agent Relay swarm topology fits a multi-agent task.
Skip if: Implementing single-agent logic or non-Agent-Relay stacks.
When should I use this skill?
You are coordinating multiple AI agents and must pick an orchestration pattern.
What you get
A justified swarm-pattern choice matched to the coordination shape of the task.
- Selected swarm pattern
- YAML or fluent-builder workflow configuration
By the numbers
- 24 swarm patterns supported
- 10 core patterns documented with topology table
Files
Overview
10 orchestration patterns for multi-agent workflows. Pick the simplest pattern that solves the problem — add complexity only when the system proves it's insufficient.
Quick Decision Framework
```
Is the task independent per agent?
YES → fan-out (parallel workers)
Does each step need the previous step's output?
YES → Is it strictly linear?
YES → pipeline
NO → dag (parallel where possible)
Does a coordinator need to stay alive and adapt?
YES → Is there one level of management?
YES → hub-spoke
NO → hierarchical (multi-level)
Is the task about making a decision?
YES → Do agents need to argue opposing sides?
YES → debate (adversarial)
NO → consensus (cooperative voting)
Does the right specialist emerge during processing?
YES → handoff (dynamic routing)
Do all agents need to freely collaborate?
YES → mesh (peer-to-peer)
Is cost the primary concern?
YES → cascade (cheap model first, escalate if needed)Pattern Reference
| # | Pattern | Topology | Agents | Best For |
|---|---|---|---|---|
| 1 | fan-out | Star (SDK center) | N parallel | Independent subtasks (reviews, research, tests) |
| 2 | pipeline | Linear chain | Sequential | Ordered stages (design → implement → test) |
| 3 | hub-spoke | Star (live hub) | 1 lead + N workers | Dynamic coordination, lead reviews/adjusts |
| 4 | consensus | Broadcast + vote | N voters | Architecture decisions, approval gates |
| 5 | mesh | Fully connected | N peers | Brainstorming, collaborative debugging |
| 6 | handoff | Routing chain | 1 active at a time | Triage, specialist routing, support flows |
| 7 | cascade | Tiered escalation | Cheapest → most capable | Cost optimization, production workloads |
| 8 | dag | Dependency graph | Parallel + joins | Complex projects with mixed dependencies |
| 9 | debate | Adversarial rounds | 2+ debaters + judge | Rigorous evaluation, architecture trade-offs |
| 10 | hierarchical | Tree (multi-level) | Lead → coordinators → workers | Large teams, domain separation |
Pattern Details
1. fan-out — Parallel Workers
fanOut([
{ task: "Review auth.ts", name: "AuthReviewer" },
{ task: "Review db.ts", name: "DbReviewer" },
], { cli: "claude" });2. pipeline — Sequential Stages
pipeline([
{ task: "Design the API schema", name: "Designer" },
{ task: "Implement the endpoints", name: "Implementer" },
{ task: "Write integration tests", name: "Tester" },
]);3. hub-spoke — Persistent Coordinator
hubAndSpoke({
hub: { task: "Coordinate building a REST API", name: "Lead" },
workers: [
{ task: "Build database models", name: "DbWorker" },
{ task: "Build route handlers", name: "ApiWorker" },
],
});4. consensus — Cooperative Voting
consensus({
proposal: "Should we migrate to Fastify?",
voters: [
{ task: "Evaluate performance", name: "PerfExpert" },
{ task: "Evaluate DX", name: "DxExpert" },
],
consensusType: "majority",
});5. mesh — Peer Collaboration
mesh({
goal: "Debug the auth flow returning 500",
agents: [
{ task: "Check server logs", name: "LogAnalyst" },
{ task: "Review auth code", name: "CodeReviewer" },
{ task: "Write repro test", name: "Tester" },
],
});6. handoff — Dynamic Routing
handoff({
entryPoint: { task: "Triage the request", name: "Triage" },
routes: [
{ agent: { task: "Handle billing", name: "Billing" }, condition: "billing, payment" },
{ agent: { task: "Handle tech issues", name: "TechSupport" }, condition: "error, bug" },
],
maxHandoffs: 3,
});7. cascade — Cost-Aware Escalation
cascade({
tiers: [
{ agent: { task: "Answer this", cli: "claude" }, confidenceThreshold: 0.7, costWeight: 1 },
{ agent: { task: "Answer this", cli: "claude" }, confidenceThreshold: 0.85, costWeight: 5 },
{ agent: { task: "Answer this", cli: "claude" }, costWeight: 20 },
],
});8. dag — Directed Acyclic Graph
dag({
nodes: [
{ id: "scaffold", task: "Create project scaffold" },
{ id: "frontend", task: "Build React UI", dependsOn: ["scaffold"] },
{ id: "backend", task: "Build API", dependsOn: ["scaffold"] },
{ id: "integrate", task: "Wire together", dependsOn: ["frontend", "backend"] },
],
maxConcurrency: 3,
});9. debate — Adversarial Refinement
debate({
topic: "Monorepo vs polyrepo for the new platform?",
debaters: [
{ task: "Argue for monorepo", position: "monorepo" },
{ task: "Argue for polyrepo", position: "polyrepo" },
],
judge: { task: "Judge and decide", name: "ArchJudge" },
maxRounds: 3,
});10. hierarchical — Multi-Level Delegation
hierarchical({
agents: [
{ id: "lead", task: "Coordinate full-stack app", role: "lead" },
{ id: "fe-coord", task: "Manage frontend", role: "coordinator", reportsTo: "lead" },
{ id: "be-coord", task: "Manage backend", role: "coordinator", reportsTo: "lead" },
{ id: "fe-dev", task: "Build components", role: "worker", reportsTo: "fe-coord" },
{ id: "be-dev", task: "Build API", role: "worker", reportsTo: "be-coord" },
],
});Reflection Protocol
All patterns support reflection — periodic synthesis that enables course correction. Enabled via reflectionThreshold on WorkflowOptions.
{
reflectionThreshold: 10, // trigger after 10 agent messages
onReflect: async (ctx) => {
// Examine ctx.recentMessages, ctx.agentStatuses
// Return adjustments or null
},
}Common Mistakes
| Mistake | Why It Fails | Fix |
|---|---|---|
| Using mesh for everything | O(n^2) communication, debugging nightmare | Use hub-spoke for most tasks |
| Pipeline for independent work | Sequential bottleneck | Use fan-out or dag |
| Hub-spoke for simple parallel tasks | Hub is unnecessary overhead | Use fan-out |
| Consensus for non-decisions | Voting on implementation tasks wastes time | Use hub-spoke, let lead decide |
| No circuit breaker on handoff | Infinite routing loops | Always set maxHandoffs |
| Cascade without confidence parsing | Agents don't report confidence | Convention injection handles this |
| Hierarchical for 3 agents | Management overhead exceeds benefit | Use hub-spoke for small teams |
DAG Executor — Proven Pattern
Agent Completion: Detect → Release → Collect
Agent writes summary file → Orchestrator polls (5s) → Detects new mtime →
Reads summary → Calls client.release(agent) → agent_exited fires → Node marked completeState & Resume
saveState(completed, depsOutput, results, startTime);
// Restart with --resume to skip completed nodesYAML Workflow Definition
Any pattern can be defined in YAML for portability:
version: "1.0"
name: feature-dev
pattern: hub-spoke
agents:
- id: lead
role: lead
cli: claude
- id: developer
role: worker
cli: codex
reportsTo: lead
steps:
- id: plan
agent: lead
prompt: "Create a development plan for: {{task}}"
expects: "PLAN_COMPLETE"
- id: implement
agent: developer
dependsOn: [plan]
prompt: "Implement: {{steps.plan.output}}"
expects: "DONE"
reflection:
enabled: true
threshold: 10
trajectory:
enabled: trueRelated skills
FAQ
How many swarm patterns does it cover?
The Agent Relay SDK supports 24 swarm patterns via a single swarm.pattern field, with 10 core patterns detailed.
How are patterns configured?
Declaratively in YAML or programmatically via the workflow() fluent builder, both hitting the same WorkflowRunner.