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 avmnu-sng/sutra --skill architecture-reviewgit clone --depth 1 https://github.com/avmnu-sng/sutraWrote 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/avmnu-sng/sutra/architecture-review)<a href="https://agentmods.dev/skills/avmnu-sng/sutra/architecture-review"><img src="https://agentmods.dev/badge/skills/avmnu-sng/sutra/architecture-review/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/avmnu-sng/sutra/architecture-review"><img src="https://agentmods.dev/badge/skills/avmnu-sng/sutra/architecture-review.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 | $0.00044 | $0.02050 |
| Opus 5 | $0.00022 | $0.01025 |
| Sonnet 5 | $0.00009 | $0.00410 |
| Haiku 4.5 | $0.00004 | $0.00205 |
Grade A, and why
architecture-review 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 11d 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 — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Architecture review
Review a backend or service architecture with this 7-point methodology, applied in order. Do not skip ahead: each step feeds the next. The goal is not a component inventory -- it is a judgment about how the system behaves under load, where it breaks, and what is worth changing.
Scope: This methodology assumes a horizontally-scaled network service. For a monolith, embedded, or desktop system, apply the request-trace and component-interaction analysis and skip the autoscaling-specific steps (pod budgets, HPA metrics, scale-to-zero).
Core principle: system behavior emerges from component interactions, not from individual component properties. A per-component analysis that misses shared limits, cascades, and contention is wrong by construction. Two components that each look healthy in isolation can deadlock, starve a shared pool, or amplify each other's retries. Analyze the seams, not just the boxes.
When to use / When not to
- Use when asked to assess scalability, capacity, resource sizing, cost, or reliability of a service or set of services; before a scaling event; when latency or cost is climbing without an obvious cause; when choosing a deployment model.
- Do not use for line-level code review, security review, or feature design. This is a systems-behavior review, not a correctness or style pass.
1. Trace every request end to end
Pick one request type and follow it through every layer. Produce a trace, not a summary.
For each distinct request type, walk:
- Entry point (which handler, which route, what triggers it).
- Every downstream call (services, databases, caches, queues, external APIs).
- Every I/O operation (disk read/write, network round trip, serialization).
- Every decision branch (and which branch is the common case vs the tail).
- Every lock, mutex, semaphore, or shared pool it touches, and for how long it holds them.
- Every retry, timeout, and backoff, with the actual values.
- Every error path -- what is caught, what is retried, what propagates, what is silently swallowed.
- The final side effect (the write, the message published, the response returned).
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.
- 11d ago First seen · 132 lines · 44 tokens per session scan A 09f4d49c0e4d
architecture-review is a skill published in the GitHub repository avmnu-sng/sutra (2 stars, last pushed 1mo ago), licensed MIT. It adds 44 tokens to every session and 2,050 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 2026-08-31.
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