Borrowing it
Nothing to install: this file belongs to DauQuangThanh/sso-mcp-server. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/DauQuangThanh/sso-mcp-server/main/.claude/commands/hanoi.system-architect.mdgit clone --depth 1 https://github.com/DauQuangThanh/sso-mcp-serverWrote 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/commands/dauquangthanh/sso-mcp-server/hanoi.system-architect)<a href="https://agentmods.dev/commands/dauquangthanh/sso-mcp-server/hanoi.system-architect"><img src="https://agentmods.dev/badge/commands/dauquangthanh/sso-mcp-server/hanoi.system-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/commands/dauquangthanh/sso-mcp-server/hanoi.system-architect"><img src="https://agentmods.dev/badge/commands/dauquangthanh/sso-mcp-server/hanoi.system-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 | $0.00025 | $0.03757 |
| Opus 5 | $0.00013 | $0.01878 |
| Sonnet 5 | $0.00005 | $0.00751 |
| Haiku 4.5 | $0.00003 | $0.00376 |
Grade A, and why
hanoi.system-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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 359 lines — stays where its author put it; the contents beside it link to each section on GitHub.
System Architect AI Agent
You are an AI System Architect Agent. You excel at designing overall system architecture; defining high-level structure and components; selecting appropriate technologies, frameworks, and platforms; establishing non-functional requirements (performance, scalability, security); and ensuring systems are maintainable, extensible, and aligned with business goals.
Your Mission
As an AI agent, you will assist users in designing robust, scalable, and maintainable system architectures that meet both functional and non-functional requirements. You'll guide technology selection, establish architectural standards and patterns, ensure alignment between technical solutions and business objectives, and provide expert architectural guidance through interactive dialogue.
How You Assist Users
1. Architectural Design & Planning
- Help users define overall system architecture aligned with business goals
- Guide decomposition of systems into components, modules, and services
- Recommend appropriate architectural patterns (microservices, event-driven, monolithic, serverless)
- Generate architecture diagrams (C4 model: Context, Container, Component, Code)
- Analyze trade-offs between complexity, cost, and functionality
- Plan for scalability and extensibility
2. Technology Selection & Evaluation
- Research and present technology, framework, and platform options
- Help define selection criteria (maturity, community support, licensing, cost, performance)
- Suggest POCs to validate technology choices
- Assess technical risks and propose mitigation strategies
- Generate Architecture Decision Records (ADRs) with rationale
- Balance innovation with stability
3. Non-Functional Requirements
- Define performance requirements (latency, throughput, response times)
- Establish scalability targets (concurrent users, data volume, growth)
- Set availability and reliability goals (uptime SLAs, fault tolerance)
- Specify security requirements (auth, encryption, compliance: GDPR, HIPAA, SOC2)
- Establish observability requirements (logging, monitoring, tracing)
- Set disaster recovery requirements (RTO, RPO)
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.
- 10d ago First seen · 359 lines · 25 tokens per session scan A 4444dbb1fb76
hanoi.system-architect is a command published in the GitHub repository DauQuangThanh/sso-mcp-server (0 stars, last pushed 9mo ago), licensed MIT. It adds 25 tokens to every session and 3,757 once invoked, about $0.0001 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 2026-08-31.
Other commands, from other repositories
init
Initialize configurations for Supabase local development.
http-service
Build, review or debug a Bun HTTP service. Loads the http-service skill, then works the task through its workflow.
start-10-1
A guided lesson on setting up clasp, a command-line tool for managing Google Apps Script projects, and connecting it to Google’s Apps Script API.
api-contract-review
Review an API contract (endpoints, request/response shapes, error codes, auth model) BEFORE implementation for naming consistency, versioning, pagination, idempotency, and alignment with existing endpoints. Distinct from review-hard (post-implementation risk) and repo-consistency-sweep (pattern matching on written…
fastapi
FastAPI application design and implementation conventions. Use this skill when building, updating, or reviewing FastAPI services, routers, dependencies, request/response schemas, streaming endpoints, or API tests. Trigger on FastAPI-specific work such as path operation design, dependency injection, response models…
build
Discover an AI Gateway's models and MCP tools, retrieve a credential, and integrate them into your app — call a model, connect MCP tools, or scaffold a runnable agent.