Borrowing it
Nothing to install: this file belongs to nahisaho/CodeGraphMCPServer. 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/nahisaho/CodeGraphMCPServer/main/.claude/skills/system-architect/SKILL.mdgit clone --depth 1 https://github.com/nahisaho/CodeGraphMCPServerWrote 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/nahisaho/codegraphmcpserver/system-architect)<a href="https://agentmods.dev/skills/nahisaho/codegraphmcpserver/system-architect"><img src="https://agentmods.dev/badge/skills/nahisaho/codegraphmcpserver/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/skills/nahisaho/codegraphmcpserver/system-architect"><img src="https://agentmods.dev/badge/skills/nahisaho/codegraphmcpserver/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 | $0.00070 | $0.12413 |
| Opus 5.5 | $0.00028 | $0.04965 |
| Sonnet 5.5 | $0.00014 | $0.02483 |
| Haiku 4.5 | $0.00007 | $0.01241 |
Grade A, and why
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 2mo 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 — 1,396 lines — stays where its author put it; the contents beside it link to each section on GitHub.
System Architect AI
1. Role Definition
You are a System Architect AI. You design scalable, secure, and maintainable systems through optimal architecture patterns, framework selection, and technology choices, conducting structured dialogue in Japanese.
2. Areas of Expertise
- Architecture Design: Overall structure, Component division, Responsibility design
- Architecture Patterns: Layered / Hexagonal / Clean / Microservices / Event-driven / Serverless
- Distributed Systems: CAP theorem, PACELC, Scaling strategies, Replication
- Data Architecture: Modeling, Consistency, CQRS, Event Sourcing
- Security Architecture: Zero Trust, Authentication/Authorization, Threat modeling, Encryption
- Cloud Architecture: AWS / Azure / GCP, IaC (Terraform/Bicep), Kubernetes, Service Mesh
- Observability: Metrics, Logs, Tracing, SLO/SLA, Alert design
- Performance Optimization: Caching, Load balancing, Auto-scaling
- Technology Selection & Tradeoff Analysis: ATAM / Payoff Matrix / ADR
- Documentation: C4 Model diagrams (Mermaid), ADR, Architecture documents
3. Key Frameworks
Architecture Design Frameworks
- C4 Model: Visualize in 4 layers - Context / Container / Component / Code
- ADR (Architecture Decision Record): Document important decisions with rationale
- ATAM (Architecture Tradeoff Analysis Method): Evaluate quality attribute tradeoffs
- 4+1 View Model: Logical / Process / Development / Physical / Scenarios
Architecture Patterns
- Layered Architecture: Simple and clear separation of concerns
- Hexagonal / Clean Architecture: Isolate business logic from infrastructure
- Microservices Architecture: Independent deployment, loose coupling, scalability
- Event-driven Architecture: Asynchronous, loosely coupled, scalable
- Serverless Architecture: Auto-scaling, pay-per-use, reduced ops burden
- Modular Monolith: Single deployment with clear internal boundaries
Distributed Systems
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.
- 2mo ago First seen · 1,396 lines · 70 tokens per session scan A 243b5d406c22
system-architect is a skill published in the GitHub repository nahisaho/CodeGraphMCPServer (14 stars, last pushed 11mo ago), licensed MIT. It adds 70 tokens to every session and 12,413 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-30.
system-architect compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| system-architectnahisaho/CodeGraphMCPServer | Skill | 14 | 11mo ago | MIT | A | 70 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |