Registry indexed
Use when coordinating multiple AI agents with Agent Relay's workflow engine and need to pick the right orchestration pattern - covers the 10 core patterns (fan-out, pipeline, hub-spoke, consensus, mesh, handoff, cascade, dag, debate, hierarchical) plus 14 specialized ones, with d
Use when coordinating multiple AI agents with Agent Relay's workflow engine and need to pick the right orchestration pattern - covers the 10 core patterns (fan-out, pipeline, hub-spoke, consensus, mesh, handoff, cascade, dag, debate, hierarchical) plus 14 specialized ones, with decision framework and accurate workflow/YAML examples.
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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.
import { runWorkflow } from '@relayflows/core';
const run = await runWorkflow('workflows/feature-dev.yaml', {
vars: { task: 'Add OAuth login' },
});
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.
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)
| # | Pattern | Topology (actual edges) | Best For |
|---|---|---|---|
| 1 | fan-out | Hub broadcasts to N workers; workers reply to hub only | Independent subtasks (reviews, research, tests) |
| 2 | pipeline | Linear chain (agenti → agent{i+1}) | Ordered stages (design → implement → test) |
| 3 | hub-spoke | Hub ↔ spokes (bidirectional); no spoke-to-spoke | Dynamic coordination, lead reviews/adjusts |
| 4 | consensus | Full mesh; decision via coordination.consensusStrategy | Architecture decisions, approval gates |
| 5 | mesh | Full mesh (every agent ↔ every other) | Brainstorming, collaborative debugging |
| 6 | handoff | Chain; passes control forward | Triage, specialist routing |
| 7 | cascade | Chain of dependsOn steps; all run on success, downstream skipped on upstream failure (no built-in "fall through") | Cost optimization: cheap first, each step's prompt passes through or redoes |
| 8 | dag | Edges from step dependsOn | Mixed dependencies, parallel where possible |
| 9 | debate | Full mesh (same topology as mesh; roles drive behavior) | Rigorous adversarial examination |
| 10 | hierarchical | Hub + subordinates (single-level in current impl) | Large teams; semantic distinction from hub-spoke |
Heads up:
hierarchicalresolves to the same edge structure ashub-spokeincoordinator.ts:313-319. Multi-level tree topology is not currently implemented — use pattern name for intent, but expect the same runtime graph.
These 14 additional patterns exist in SwarmPattern (types.ts:114-139). The coordinator has role-based auto-selection heuristics (coordinator.ts:51-165), but they only fire when swarm.pattern is omitted — YAML validation requires it (runner.ts:2105-2117), so auto-selection is effectively a programmatic-API feature. In YAML, set swarm.pattern explicitly.
Topology is still resolved per-pattern once selected; the "Triggering roles" column reflects what the coordinator looks for to shape edges (per coordinator.ts:250-450):
| Pattern | Roles the topology keys off | Topology |
|---|---|---|
map-reduce | mapper + reducer | coordinator → mappers → reducers → coordinator |
scatter-gather | — | hub → workers → hub |
supervisor | supervisor | supervisor ↔ workers |
reflection | critic or reviewer (auto-select uses critic only) | producers → critic → producers (loop) |
red-team | attacker/red-team + defender/blue-team | adversarial mesh with optional judges |
verifier | verifier | producers → verifiers → back to producers |
auction | auctioneer | auctioneer → bidders → auctioneer |
escalation | tier-* | tiered chain, escalate up / report down |
saga | saga-orchestrator, compensate-handler | orchestrator ↔ participants |
circuit-breaker | primary + fallback/backup | try primary, fallback on failure |
blackboard | blackboard / shared-workspace | shared state hub |
swarm | hive-mind / swarm-agent | stigmergy-style |
competitive | — (declared explicitly) | independent parallel implementations + judge |
review-loop | implement* + 2+ reviewer* | implementer ↔ reviewers |
supervisor or hub-spoke when a lead needs to coordinate live squads.review-loop when the main risk is code quality and feedback iteration.reflection when critic feedback should loop directly back to producers.verifier when completion evidence matters more than design debate.competitive only when independent alternative implementations are useful; otherwise split by ownership scope.await workflow('review')
.pattern('fan-out')
.agent('lead', { cli: 'claude', role: 'lead' })
.agent('auth-rev', { cli: 'claude', role: 'worker', interactive: false })
.agent('db-rev', { cli: 'claude', role: 'worker', interactive: false })
.step('review-auth', { agent: 'auth-rev', task: 'Review auth.ts' })
.step('review-db', { agent: 'db-rev', task: 'Review db.ts' })
.run();
swarm: { pattern: pipeline }
agents:
- { name: designer, cli: claude }
- { name: implementer, cli: codex, interactive: false }
- { name: tester, cli: codex, interactive: false }
workflows:
- name: build
steps:
- {
name: design,
agent: designer,
task: 'Design the API schema',
verification: { type: output_contains, value: DONE },
}
- {
name: implement,
agent: implementer,
dependsOn: [design],
task: 'Implement: {{steps.design.output}}',
}
- { name: test, agent: tester, dependsOn: [implement], task: 'Write integration tests' }
await workflow('api-build')
.pattern('hub-spoke')
.channel('swarm-api')
.agent('lead', { cli: 'claude', role: 'lead' })
.agent('db-worker', { cli: 'claude', role: 'worker' }) // interactive by default — hub DMs it
.agent('api-worker', { cli: 'claude', role: 'worker' }) // interactive by default — hub DMs it
.step('models', { agent: 'db-worker', task: 'Build database models' })
.step('routes', { agent: 'api-worker', task: 'Build route handlers', dependsOn: ['models'] })
.step('review', { agent: 'lead', task: 'Review everything', dependsOn: ['routes'] })
.run();
swarm: { pattern: consensus }
agents:
- { name: perf, cli: claude, role: reviewer }
- { name: dx, cli: claude, role: reviewer }
- { name: sec, cli: claude, role: reviewer }
coordination:
consensusStrategy: majority # declarative marker: majority | unanimous | quorum
votingThreshold: 0.66
workflows:
- name: decide
steps:
- { name: evaluate-perf, agent: perf, task: 'Evaluate perf of
name: choosing-swarm-patterns description: Use when coordinating multiple AI agents with Agent Relay's workflow engine and need to pick the right orchestration pattern - covers the 10 core patterns (fan-out, pipeline, hub-spoke, consensus, mesh, handoff, cascade, dag, debate, hierarchical) plus 14 specialized ones, with decision framework and accurate workflow/YAML examples.
---
name: choosing-swarm-patterns
description: Use when coordinating multiple AI agents with Agent Relay's workflow engine and need to pick the right orchestration pattern - covers the 10 core patterns (fan-out, pipeline, hub-spoke, consensus, mesh, handoff, cascade, dag, debate, hierarchical) plus 14 specialized ones, with decision framework and accurate workflow/YAML examples.
---
### 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):**
```ts
import { runWorkflow } from '@relayflows/core';
const run = await runWorkflow('workflows/feature-dev.yaml', {
vars: { task: 'Add OAuth login' },
});
```
#### **2. Fluent builder (programmatic):**
```ts
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)
```
### Pattern Reference (Core 10)
| # | Pattern | Topology (actual edges) | Best For |
| --- | ---------------- | ------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------- |
| 1 | **fan-out** | Hub broadcasts to N workers; workers reply to hub only | Independent subtasks (reviews, research, tests) |
| 2 | **pipeline** | Linear chain (agent*i → agent*{i+1}) | Ordered stages (design → implement → test) |
| 3 | **hub-spoke** | Hub ↔ spokes (bidirectional); no spoke-to-spoke | Dynamic coordination, lead reviews/adjusts |
| 4 | **consensus** | Full mesh; decision via `coordination.consensusStrategy` | Architecture decisions, approval gates |
| 5 | **mesh** | Full mesh (every agent ↔ every other) | Brainstorming, collaborative debugging |
| 6 | **handoff** | Chain; passes control forward | Triage, specialist routing |
| 7 | **cascade** | Chain of `dependsOn` steps; all run on success, downstream skipped on upstream failure (no built-in "fall through") | Cost optimization: cheap first, each step's prompt passes through or redoes |
| 8 | **dag** | Edges from step `dependsOn` | Mixed dependencies, parallel where possible |
| 9 | **debate** | Full mesh (same topology as mesh; roles drive behavior) | Rigorous adversarial examination |
| 10 | **hierarchical** | Hub + subordinates (single-level in current impl) | Large teams; semantic distinction from hub-spoke |
> **Heads up:** `hierarchical` resolves to the same edge structure as `hub-spoke` in `coordinator.ts:313-319`. Multi-level tree topology is not currently implemented — use pattern name for intent, but expect the same runtime graph.
### Additional Patterns (role-driven)
These 14 additional patterns exist in `SwarmPattern` (types.ts:114-139). The coordinator has role-based auto-selection heuristics (`coordinator.ts:51-165`), but they only fire when `swarm.pattern` is **omitted** — YAML validation requires it (`runner.ts:2105-2117`), so auto-selection is effectively a programmatic-API feature. In YAML, set `swarm.pattern` explicitly.
Topology is still resolved per-pattern once selected; the "Triggering roles" column reflects what the coordinator looks for to shape edges (per `coordinator.ts:250-450`):
| Pattern | Roles the topology keys off | Topology |
| ----------------- | ------------------------------------------------------- | ---------------------------------------------- |
| `map-reduce` | `mapper` + `reducer` | coordinator → mappers → reducers → coordinator |
| `scatter-gather` | — | hub → workers → hub |
| `supervisor` | `supervisor` | supervisor ↔ workers |
| `reflection` | `critic` or `reviewer` (auto-select uses `critic` only) | producers → critic → producers (loop) |
| `red-team` | `attacker`/`red-team` + `defender`/`blue-team` | adversarial mesh with optional judges |
| `verifier` | `verifier` | producers → verifiers → back to producers |
| `auction` | `auctioneer` | auctioneer → bidders → auctioneer |
| `escalation` | `tier-*` | tiered chain, escalate up / report down |
| `saga` | `saga-orchestrator`, `compensate-handler` | orchestrator ↔ participants |
| `circuit-breaker` | `primary` + `fallback`/`backup` | try primary, fallback on failure |
| `blackboard` | `blackboard` / `shared-workspace` | shared state hub |
| `swarm` | `hive-mind` / `swarm-agent` | stigmergy-style |
| `competitive` | — (declared explicitly) | independent parallel implementations + judge |
| `review-loop` | `implement*` + 2+ `reviewer*` | implementer ↔ reviewers |
### Structured Squad Review Loop
- Split the work into bounded implementation squads. Each squad owns a non-overlapping file or subsystem scope.
- Give each squad an implementer plus a shadow/review partner. The shadow follows the implementer in real time, checks alignment with the spec, and posts concise feedback before the work drifts.
- Require the implementer to self-reflect before external review: compare the final diff against the spec, AGENTS.md / CLAUDE.md, recent local conventions, tests, and declared non-goals.
- Run an independent self-review/fresh-eyes agent that reads the actual files and recent repo context, not just the chat transcript.
- Send that review back to the implementer for one repair round.
- After squads converge, run a final two-agent review team, usually one Claude reviewer and one Codex reviewer, independently. They compare notes, merge findings, and produce one final verdict.
- Spawn fresh fix agents for final-review findings. Those fix agents self-reflect, then the final reviewers re-check the post-fix state until the spec is fully satisfied or a blocker is documented.
- Use `supervisor` or `hub-spoke` when a lead needs to coordinate live squads.
- Use `review-loop` when the main risk is code quality and feedback iteration.
- Use `reflection` when critic feedback should loop directly back to producers.
- Use `verifier` when completion evidence matters more than design debate.
- Use `competitive` only when independent alternative implementations are useful; otherwise split by ownership scope.
### Pattern Details
#### 1. fan-out — Parallel Workers
```ts
await workflow('review')
.pattern('fan-out')
.agent('lead', { cli: 'claude', role: 'lead' })
.agent('auth-rev', { cli: 'claude', role: 'worker', interactive: false })
.agent('db-rev', { cli: 'claude', role: 'worker', interactive: false })
.step('review-auth', { agent: 'auth-rev', task: 'Review auth.ts' })
.step('review-db', { agent: 'db-rev', task: 'Review db.ts' })
.run();
```
#### 2. pipeline — Sequential Stages
```yaml
swarm: { pattern: pipeline }
agents:
- { name: designer, cli: claude }
- { name: implementer, cli: codex, interactive: false }
- { name: tester, cli: codex, interactive: false }
workflows:
- name: build
steps:
- {
name: design,
agent: designer,
task: 'Design the API schema',
verification: { type: output_contains, value: DONE },
}
- {
name: implement,
agent: implementer,
dependsOn: [design],
task: 'Implement: {{steps.design.output}}',
}
- { name: test, agent: tester, dependsOn: [implement], task: 'Write integration tests' }
```
#### 3. hub-spoke — Persistent Coordinator
```ts
await workflow('api-build')
.pattern('hub-spoke')
.channel('swarm-api')
.agent('lead', { cli: 'claude', role: 'lead' })
.agent('db-worker', { cli: 'claude', role: 'worker' }) // interactive by default — hub DMs it
.agent('api-worker', { cli: 'claude', role: 'worker' }) // interactive by default — hub DMs it
.step('models', { agent: 'db-worker', task: 'Build database models' })
.step('routes', { agent: 'api-worker', task: 'Build route handlers', dependsOn: ['models'] })
.step('review', { agent: 'lead', task: 'Review everything', dependsOn: ['routes'] })
.run();
```
#### 4. consensus — Cooperative Voting
```yaml
swarm: { pattern: consensus }
agents:
- { name: perf, cli: claude, role: reviewer }
- { name: dx, cli: claude, role: reviewer }
- { name: sec, cli: claude, role: reviewer }
coordination:
consensusStrategy: majority # declarative marker: majority | unanimous | quorum
votingThreshold: 0.66
workflows:
- name: decide
steps:
- { name: evaluate-perf, agent: perf, task: 'Evaluate perf of Source needs review
The tracked source changed or could not be synchronized. Review the current source before installing.
Review before install: Avoid automatic install
Listed tools are metadata hints, not tested compatibility. Agent prompts are suggested handoffs.
Check the source for dependencies, API keys and third-party costs. A public repository does not mean every service is free.
Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.
Version reported in registry metadata; check source releases before relying on it.
Quality
76/100
Strong
Trust
59/100
Do not auto-install
Audit
77/100
Needs review
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
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},
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"endpoint": "https://www.openagentskill.com/api/agent/outcome",
"method": "POST",
"requires_resolve_event_id": true,
"event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
"expected_outcomes": [
"success",
"failed",
"not_relevant",
"blocked_by_risk",
"setup_required"
],
"payload_template": {
"event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
"skill_slug": "agentworkforce-choosing-swarm-patterns",
"task": "Use choosing-swarm-patterns in an agent workflow",
"agent": "codex",
"outcome": "success",
"install_used": true,
"risk_blocked": false,
"setup_required": false,
"task_success": true,
"output_quality": 4,
"error_type": null,
"human_review_required": false,
"workspace": "sandbox",
"time_to_useful_ms": 120000,
"notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
}
},
"endpoints": {
"web": "https://www.openagentskill.com/skills/agentworkforce-choosing-swarm-patterns",
"api": "https://www.openagentskill.com/api/agent/skills/agentworkforce-choosing-swarm-patterns",
"audit": "https://www.openagentskill.com/skills/agentworkforce-choosing-swarm-patterns/audit",
"eval": "https://www.openagentskill.com/api/agent/evals?slug=agentworkforce-choosing-swarm-patterns&task=Use%20choosing-swarm-patterns%20in%20an%20agent%20workflow&max_risk=medium",
"resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20choosing-swarm-patterns%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
"receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20choosing-swarm-patterns%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
"install": "https://www.openagentskill.com/api/skills/agentworkforce-choosing-swarm-patterns/install",
"manifest": "https://www.openagentskill.com/api/registry/manifest/agentworkforce-choosing-swarm-patterns"
}
}Listing source
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