# multi-agent-patterns

Architectural guide for designing multi-agent setups. Helps isolate contexts, pick coordination topologies, and budget token overhead.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 305 installs · ★ 981
- Author: guanyang
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/guanyang/open-agent-hub/tree/HEAD/skills/multi-agent-patterns/SKILL.md
- Updated: 2026-10-25
- HTML: https://affpapa.org/en/nevibecode/skills/guanyang-multi-agent-patterns

## What it does

The skill guides the design of multi-agent systems when a single context window degrades under task complexity. It outlines three core topologies: supervisor orchestrators, peer-to-peer swarms with explicit handoffs, and hierarchical execution layers. Sub-agents are framed strictly around context isolation rather than anthropomorphic role-playing.

It focuses directly on attention scarcity, context poisoning, and the telephone game where supervisors paraphrase sub-agent outputs incorrectly. To solve this, the skill details a `forward_message` pattern that passes worker outputs directly to users: benchmark data shows supervisor setups can perform roughly 50% worse without direct forwarding.

Multi-agent setups multiply token consumption significantly compared to single-agent baselines. The skill focuses on coordination topologies and deliberately excludes hosted sandboxes, KV-cache compaction, and tool design, which belong to separate skills.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add guanyang/open-agent-hub --skill multi-agent-patterns -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/multi-agent-patterns/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/multi-agent-patterns/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add guanyang/open-agent-hub --skill multi-agent-patterns -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/multi-agent-patterns/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add guanyang/open-agent-hub --skill multi-agent-patterns -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/multi-agent-patterns/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install guanyang/open-agent-hub multi-agent-patterns
```

2. **Manually: put the files in place**
- File: `.github/skills/multi-agent-patterns/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add guanyang/open-agent-hub --skill multi-agent-patterns -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/guanyang/open-agent-hub --path skills/multi-agent-patterns
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/multi-agent-patterns/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add guanyang/open-agent-hub --skill multi-agent-patterns -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/guanyang/open-agent-hub/tree/HEAD/skills/multi-agent-patterns/SKILL.md

## When to use it
- design coordination topologies for multiple LLM instances
- prevent fidelity loss caused by supervisor paraphrasing
- isolate context windows across independent parallel subtasks
- choose between supervisor, swarm, and hierarchical patterns

## Example prompts
- Help me design a supervisor multi-agent architecture for parallel research tasks
- How do I prevent the telephone game problem between orchestrators and workers?
- Should I use a swarm or supervisor pattern for context isolation here?

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: e536d059da60484b.

BEGIN THIRD-PARTY FILE e536d059da60484b
```text
---
name: multi-agent-patterns
description: "This skill should be used when designing multi-agent systems that need context isolation, supervisor or swarm coordination, explicit handoffs, parallel execution, or a decision on whether multiple agents are justified."
---

# Multi-Agent Architecture Patterns

Multi-agent architectures distribute work across multiple language model instances, each with its own context window. When designed well, this distribution enables capabilities beyond single-agent limits. When designed poorly, it introduces coordination overhead that negates benefits. The critical insight is that sub-agents exist primarily to isolate context, not to anthropomorphize role division.

## When to Activate

Activate this skill when:
- Single-agent context limits constrain task complexity
- Tasks decompose naturally into parallel subtasks
- Different subtasks require different tool sets or system prompts
- Building systems that must handle multiple domains simultaneously
- Scaling agent capabilities beyond single-context limits
- Designing production agent systems with multiple specialized components

Do not activate this skill for adjacent work owned by other skills:
- Deciding task-model fit, pipeline shape, or project-level cost before topology is known: `project-development`.
- Designing hosted sandboxes, warm pools, remote sessions, or background runtime infrastructure: `hosted-agents`.
- Sharing orchestrator state through KV-cache compaction in controlled runtimes: `latent-briefing`.
- Designing the tools each agent exposes: `tool-design`.

## Core Concepts

Use multi-agent patterns when a single agent's context window cannot hold all task-relevant information. Context isolation is the primary benefit — each agent operates in a clean context without accumulated noise from other subtasks, preventing the telephone game problem where information degrades through repeated summarization.

Choose among three dominant patterns based on coordination needs, not organizational metaphor:

- **Supervisor/orchestrator** — Use for centralized control when tasks have clear decomposition and human oversight matters. A single coordinator delegates to specialists and synthesizes results.
- **Peer-to-peer/swarm** — Use for flexible exploration when rigid planning is counterproductive. Any agent can transfer control to any other through explicit handoff mechanisms.
- **Hierarchical** — Use for large-scale projects with layered abstraction (strategy, planning, execution). Each layer operates at a different level of detail with its own context structure.
```
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