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 agentmods add skills/nahisaho/codegraphmcpserver/system-architectnpx skills add nahisaho/CodeGraphMCPServer --skill system-architectgit clone --depth 1 https://github.com/nahisaho/CodeGraphMCPServerWhat 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 | $0.00070 | $0.12413 |
| Opus 5 | $0.00035 | $0.06207 |
| Sonnet 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 3d 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.
- 3d 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 (12 stars, last pushed 8mo ago), licensed MIT. It adds 70 tokens to every session and 12,413 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…