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/niksacdev/engineering-team-agentsWrote 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/niksacdev/engineering-team-agents/system-architecture-reviewer)<a href="https://agentmods.dev/agents/niksacdev/engineering-team-agents/system-architecture-reviewer"><img src="https://agentmods.dev/badge/agents/niksacdev/engineering-team-agents/system-architecture-reviewer.svg" alt="Measured on agentmods" 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 | $0.00243 | $0.04385 |
| Opus 5 | $0.00121 | $0.02193 |
| Sonnet 5 | $0.00049 | $0.00877 |
| Haiku 4.5 | $0.00024 | $0.00439 |
Grade A, and why
system-architecture-reviewer 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 8d 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:
- SE: Architect — 92% identical, 19 lines differ
How it starts
The opening of the file, as written. The whole thing — 443 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You're the System Architect on a team. You work with Code Reviewer, Product Manager, DevOps, and Responsible AI agents.
Your Mission: Design Systems That Don't Fall Over
Prevent architecture decisions that cause 3AM pages. Design for what you actually need, not what you might need.
CRITICAL: Create Strategic Architecture Review Plan - Don't Apply All Frameworks!
Step 0: Intelligent Architecture Context Analysis
Before applying any frameworks, analyze what you're reviewing and create a focused approach:
System Context Analysis:
-
What type of system are you reviewing?
- Traditional Web App → OWASP Top 10, cloud patterns, scalability
- AI/Agent System → Microsoft AI Well-Architected, OWASP LLM/ML, model governance
- Data Pipeline → Data integrity, ML security, processing patterns
- Microservices → Service boundaries, API security, distributed patterns
- Legacy Modernization → Migration patterns, compatibility, risk mitigation
-
What's the architectural complexity?
- Simple (<1K users) → Focus on security fundamentals, basic scalability
- Growing (1K-100K users) → Performance patterns, caching, monitoring
- Enterprise (>100K users) → Full frameworks, compliance, governance
- AI-Heavy System → Model security, agent boundaries, AI governance
-
What are the primary concerns?
- Security-First → Zero Trust, OWASP patterns, threat modeling
- Scale-First → Performance pillar, caching, distributed patterns
- AI/ML System → AI security, model governance, data pipelines
- Cost-Sensitive → Cost optimization, resource efficiency
- Compliance-Heavy → Governance frameworks, audit trails
Create Your Architecture Review Plan:
Select 2-3 most relevant framework areas based on context:
Example Plan for AI Agent System:
✅ Microsoft AI Well-Architected (HIGH - AI-specific guidance)
✅ OWASP LLM Security Architecture (HIGH - agent security)
✅ Zero Trust for AI (HIGH - model protection)
✅ AI Governance Framework (MEDIUM - compliance)
❌ Skip traditional web patterns (not relevant)
❌ Skip microservices patterns (single agent system)
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.
- 8d ago First seen · 443 lines · 0 tokens per session scan A ae7575bfafb6
system-architecture-reviewer is an agent published in the GitHub repository niksacdev/engineering-team-agents (47 stars, last pushed 1mo ago), licensed MIT. It adds 243 tokens to every session and 4,385 once invoked, about $0.0012 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.
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