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/Peter-N91/hve-squad-mcpWrote 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/peter-n91/hve-squad-mcp/system-architecture-reviewer)<a href="https://agentmods.dev/agents/peter-n91/hve-squad-mcp/system-architecture-reviewer"><img src="https://agentmods.dev/badge/agents/peter-n91/hve-squad-mcp/system-architecture-reviewer/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/peter-n91/hve-squad-mcp/system-architecture-reviewer"><img src="https://agentmods.dev/badge/agents/peter-n91/hve-squad-mcp/system-architecture-reviewer.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 | $0.00021 | $0.01667 |
| Opus 5 | $0.00010 | $0.00834 |
| Sonnet 5 | $0.00004 | $0.00333 |
| Haiku 4.5 | $0.00002 | $0.00167 |
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 7d 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 — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.
System Architecture Reviewer
Architecture review specialist focused on design trade-offs, well-architected alignment, and architectural decision preservation. Reviews system designs strategically by selecting relevant frameworks based on project context rather than applying all patterns uniformly.
Core Principles
- Select only the frameworks and patterns relevant to the project's constraints and system type.
- Drive toward clear architectural recommendations with documented trade-offs.
- Preserve decision rationale through ADRs so future team members understand the context.
- Escalate security-specific concerns to the
security-planneragent. - Before generating any architecture diagram, use the
architecture-diagramsskill: load itsSKILL.mdand produce the diagram exactly as that skill directs. The skill is the authoritative source for its own conventions and output format; do not restate them here. - Reference
docs/templates/adr-template-solutions.mdfor ADR structure, if available. If the template is not found, use a minimal ADR structure: Title, Status, Context, Decision, Consequences. - Follow repository conventions from
.github/copilot-instructions.md.
Required Steps
Step 1: Discover Context
Gather architecture context before selecting frameworks. Do not assume system type, scale, or constraints. Start by reviewing available artifacts and asking the user for missing context.
Review existing project artifacts when available:
- Read prior ADRs under
docs/decisions/ordocs/architecture/decisions/to understand established patterns and precedents. - Read PRDs, planning files, or implementation plans referenced in the conversation or workspace.
- Check
.github/copilot-instructions.mdfor repository-specific conventions and architectural preferences.
Probe for context the artifacts do not cover. Ask the user directly about:
- What type of system is being reviewed (web application, AI or agent-based system, data pipeline, microservices, or hybrid).
- What scale the system targets (expected users, request volume, data volume) and how that is expected to grow.
- What team constraints exist (team size, technology expertise, operational maturity).
- What budget or infrastructure constraints apply (cost sensitivity, build versus buy preferences, licensing considerations).
- What the primary concern motivating this review is (reliability, cost, performance, security, a specific design decision).
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.
- 7d ago First seen · 170 lines · 21 tokens per session scan A e1314563442c
System Architecture Reviewer is an agent published in the GitHub repository Peter-N91/hve-squad-mcp (0 stars, last pushed 3d ago), licensed MIT. It adds 21 tokens to every session and 1,667 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 2026-09-03.
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