choosing-swarm-patterns
Use when coordinating multiple AI agents and need to pick the right orchestration pattern - covers 10 patterns (fan-out, pipeline, hub-spoke, consensus, mesh, handoff, cascade, dag, debate, hierarchical) with decision framework and reflection protocol
Best use case
choosing-swarm-patterns is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Use when coordinating multiple AI agents and need to pick the right orchestration pattern - covers 10 patterns (fan-out, pipeline, hub-spoke, consensus, mesh, handoff, cascade, dag, debate, hierarchical) with decision framework and reflection protocol
Teams using choosing-swarm-patterns should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/choosing-swarm-patterns/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How choosing-swarm-patterns Compares
| Feature / Agent | choosing-swarm-patterns | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Use when coordinating multiple AI agents and need to pick the right orchestration pattern - covers 10 patterns (fan-out, pipeline, hub-spoke, consensus, mesh, handoff, cascade, dag, debate, hierarchical) with decision framework and reflection protocol
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
### 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
```ts
fanOut([
{ task: "Review auth.ts", name: "AuthReviewer" },
{ task: "Review db.ts", name: "DbReviewer" },
], { cli: "claude" });
```
#### 2. pipeline — Sequential Stages
```ts
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
```ts
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
```ts
consensus({
proposal: "Should we migrate to Fastify?",
voters: [
{ task: "Evaluate performance", name: "PerfExpert" },
{ task: "Evaluate DX", name: "DxExpert" },
],
consensusType: "majority",
});
```
#### 5. mesh — Peer Collaboration
```ts
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
```ts
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
```ts
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
```ts
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
```ts
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
```ts
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.
```ts
{
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 complete
```
#### State & Resume
```ts
saveState(completed, depsOutput, results, startTime);
// Restart with --resume to skip completed nodes
```
### YAML Workflow Definition
#### Any pattern can be defined in YAML for portability:
```yaml
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: true
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