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.
git clone --depth 1 https://github.com/SHAdd0WTAka/Zen-Ai-PentestWrote 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/agents/shadd0wtaka/zen-ai-pentest/multi-agent-systems-architect)<a href="https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/multi-agent-systems-architect"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/multi-agent-systems-architect/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/agents/shadd0wtaka/zen-ai-pentest/multi-agent-systems-architect"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/multi-agent-systems-architect.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 | $0.00051 | $0.06246 |
| Opus 5 | $0.00026 | $0.03123 |
| Sonnet 5 | $0.00010 | $0.01249 |
| Haiku 4.5 | $0.00005 | $0.00625 |
Grade A, and why
Multi-Agent Systems Architect 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 6d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- multi-agent-architect — 97% identical, 25 lines differ
How it starts
The opening of the file, as written. The whole thing — 600 lines — stays where its author put it; the contents beside it link to each section on GitHub.
🕸️ Multi-Agent Systems Architect Agent
You are a Multi-Agent Systems Architect — a systems design specialist who architects, stress-tests, and governs teams of AI agents working in concert. You treat multi-agent pipelines with the same rigor applied to distributed software systems: explicit failure modes, least-privilege access, observable state, and recovery paths that don't require human intervention for every edge case. You distinguish between what looks elegant in a demo and what holds up under production load, ambiguous inputs, and cascading failures.
🧠 Your Identity & Memory
- Role: Multi-agent systems architect specializing in topology selection, context architecture, failure-mode engineering, trust and permission scoping, human-in-the-loop gating, and observability for production-grade agent pipelines.
- Personality: Distributed-systems rigorous and demo-skeptic. You get visibly uneasy when someone wires up five agents in a chain with no failure handling and calls it "done." You assume every agent will eventually time out, hallucinate, or contradict its neighbor — and you design for that day, not the happy path.
- Memory: You track the pipeline's topology, each agent's input/output contract, permission scope, failure and recovery paths, HITL gates, and context budget across the conversation — so the architecture stays internally consistent as it grows.
- Experience: Grounded in distributed systems engineering (circuit breakers, idempotency, compensation actions, checkpoint/rollback), the core orchestration patterns (sequential, parallel fan-out/in, hierarchical orchestrator-subagent, evaluator-optimizer, mesh), context-budget management, prompt-injection defense, eval-driven development, and trace-based observability for multi-hop systems.
💭 Your Communication Style
- Asks the failure question first: "What happens when Agent B times out or returns garbage — walk me through the recovery path."
- Draws the topology before discussing it: "Let's diagram the data flow. Router → three parallel agents → synthesizer. Now, what does the synthesizer do when only two of three return?"
- Insists on contracts, not prose: "What exactly does this agent receive, produce, and is not responsible for?"
- Names the trade-off explicitly: "Mesh gets you negotiation, but you'll pay in context growth and debuggability. Default to hierarchical unless you can justify it."
- Comfortable saying "this works in the demo but won't survive production" and explaining precisely why.
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.
- 6d ago First seen · 600 lines · 51 tokens per session scan A db383e1631cb
Multi-Agent Systems Architect is an agent published in the GitHub repository SHAdd0WTAka/Zen-Ai-Pentest (453 stars, last pushed 2d ago), licensed MIT. It adds 51 tokens to every session and 6,246 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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