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 skills add codebygarv/Ai-skills --skill architecture-reviewergit clone --depth 1 https://github.com/codebygarv/Ai-skillsWrote 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/codebygarv/ai-skills/architecture-reviewer)<a href="https://agentmods.dev/skills/codebygarv/ai-skills/architecture-reviewer"><img src="https://agentmods.dev/badge/skills/codebygarv/ai-skills/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/skills/codebygarv/ai-skills/architecture-reviewer"><img src="https://agentmods.dev/badge/skills/codebygarv/ai-skills/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 | $0.00037 | $0.00563 |
| Opus 5 | $0.00018 | $0.00282 |
| Sonnet 5 | $0.00007 | $0.00113 |
| Haiku 4.5 | $0.00004 | $0.00056 |
Grade A, and why
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 9d 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 — 37 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Review a system's architecture — how components/services are divided, how they communicate, where state lives, and how the pieces depend on each other — for scalability, coupling, and long-term maintainability, at a level above individual code review.
When to Use
- Evaluating a proposed or existing system architecture.
- Before a significant scaling milestone, to find what will break first.
- A codebase feels hard to change, and the cause seems structural rather than isolated to one file.
What to Analyze
- Separation of concerns — are responsibilities cleanly divided (data access, business logic, presentation), or is logic scattered/duplicated across layers that shouldn't need to know about each other?
- Coupling — how many places break if one component changes its interface? Tight coupling between components that should be independent is the main long-term maintainability risk.
- Scalability — what's the first component to become a bottleneck under significantly more load/data, and is that dependency structural (hard to fix later) or incidental (easy to fix later)?
- Data flow & state ownership — is it clear which component owns a given piece of state/data, or is the same data mutated from multiple places with no clear source of truth?
- Failure isolation — does one component's failure cascade to unrelated components, or is blast radius contained?
- Evolvability — how hard is it to add a plausible near-future requirement (a new integration, a new client type) given the current structure?
Output Format
- A short description of the architecture as understood, to confirm shared understanding before critiquing it.
- Findings grouped by area (Separation of Concerns, Coupling, Scalability, Data Ownership, Failure Isolation, Evolvability).
- Each finding: the structural issue, the concrete scenario where it causes pain, and a directionally concrete recommendation (not just "reduce coupling" — name the specific boundary to introduce).
- Distinguish issues worth fixing now vs. acceptable technical debt given current scale/priorities.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 37 lines · 37 tokens per session scan A 390b1066b975
architecture-reviewer is a skill published in the GitHub repository codebygarv/Ai-skills (25 stars, last pushed 20d ago), licensed MIT. It adds 37 tokens to every session and 563 once invoked, about $0.0002 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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