Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add hajekim/agentic-design-patterns-extension --skill multi-agent-collaborationgit clone --depth 1 https://github.com/hajekim/agentic-design-patterns-extensionWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/hajekim/agentic-design-patterns-extension/multi-agent-collaboration)<a href="https://agentmods.dev/skills/hajekim/agentic-design-patterns-extension/multi-agent-collaboration"><img src="https://agentmods.dev/badge/skills/hajekim/agentic-design-patterns-extension/multi-agent-collaboration/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/hajekim/agentic-design-patterns-extension/multi-agent-collaboration"><img src="https://agentmods.dev/badge/skills/hajekim/agentic-design-patterns-extension/multi-agent-collaboration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00438 | $0.03652 |
| Opus 5.5 | $0.00175 | $0.01461 |
| Sonnet 5.5 | $0.00088 | $0.00730 |
| Haiku 4.5 | $0.00044 | $0.00365 |
Grade A, and why
multi-agent-collaboration scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to multi-agent-collaboration — 3 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 383 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Multi-Agent Collaboration Pattern
Overview
The Multi-Agent Collaboration Pattern structures a system as a cooperative ensemble of distinct, specialized agents rather than a single monolithic agent. Each agent has a defined role, specific goals, and potentially unique tool access or domain knowledge. The power of this pattern lies in the interaction and synergy between agents — the collective output surpasses what any individual agent could produce alone.
Core Principle: Divide by specialization, conquer through cooperation — assign each agent what it does best, then orchestrate their collaboration.
When This Skill Applies
Activate this pattern when:
- The task spans multiple domains requiring different types of expertise
- Different phases of a workflow have fundamentally different requirements
- A single agent would be overloaded by the breadth of tools and responsibilities
- Quality improves through critic-reviewer feedback loops between agents
- Scalability demands distributing work across independent specialized units
- Tasks can be decomposed into sub-problems, each handled by a dedicated agent
Rule of thumb: Use Multi-Agent Collaboration when a task is complex enough that a human team of specialists would handle it better than a single generalist.
DEFINE → PLAN → ACTION Workflow
DEFINE
Map the collaboration requirements:
- What are the distinct sub-domains or phases of the task?
- What specialized role is needed for each sub-domain?
- How will agents communicate and hand off work?
- What is the overall orchestration model (sequential, parallel, hierarchical)?
PLAN
Design the multi-agent architecture:
- Define each agent with a clear role, goal, and tool set
- Choose the communication structure (Sequential, Network, Supervisor, Hierarchical, Custom)
- Design the handoff protocol: how does one agent's output become the next agent's input?
- Plan for agent failure: what happens if one specialist agent fails?
- Define the aggregation/synthesis step that produces the final unified output
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 383 lines · 438 tokens per session scan A aef25826856e
multi-agent-collaboration is a skill published in the GitHub repository hajekim/agentic-design-patterns-extension (1 stars, last pushed 6mo ago), licensed MIT. It adds 438 tokens to every session and 3,652 once invoked, about $0.0018 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to multi-agent-collaboration, differing in 3 lines, and is treated as a copy.
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