system-design-review

system-design-review is a skill for Claude Code, Codex from HoangNguyen0403/agent-skills-standard. It costs 55 tokens per session (827 once invoked), scanned A, original, MIT.

A system-architecture audit skill that scores a proposed or existing design across requirements, capacity, redundancy, data scaling, caching, asynchronous work, monitoring, and rollout.

In plain words
What is it for?
Use it to review a design document or running system, identify weaknesses such as untested failover or missing capacity numbers, and create a prioritized improvement plan.
Why use it?
It turns missing evidence and operational risks into a clear verdict instead of treating an architecture as complete because it sounds reasonable.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

Good fit Use it to review a design document or running system, identify weaknesses such as untested failover or missing capacity numbers, and create a prioritized improvement plan.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/hoangnguyen0403/agent-skills-standard/system-design-review
Install

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.

Any agent
npx skills add HoangNguyen0403/agent-skills-standard --skill system-design-review
Clone the repo
git clone --depth 1 https://github.com/HoangNguyen0403/agent-skills-standard

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for system-design-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/hoangnguyen0403/agent-skills-standard/system-design-review/github.svg)](https://agentmods.dev/skills/hoangnguyen0403/agent-skills-standard/system-design-review)
Your own site
<a href="https://agentmods.dev/skills/hoangnguyen0403/agent-skills-standard/system-design-review"><img src="https://agentmods.dev/badge/skills/hoangnguyen0403/agent-skills-standard/system-design-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.

agentmods 80×15 button for system-design-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/hoangnguyen0403/agent-skills-standard/system-design-review"><img src="https://agentmods.dev/badge/skills/hoangnguyen0403/agent-skills-standard/system-design-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 55 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 827 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00055 $0.00827
Opus 5 $0.00028 $0.00413
Sonnet 5 $0.00011 $0.00165
Haiku 4.5 $0.00006 $0.00083

Measured 12d ago against content hash c7b824bff9dc, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

system-design-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 12d 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.

.agents/skills/system-design/system-design-review/SKILL.md · 69 lines

How it starts

The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.

System Design Review

Priority: P1 (HIGH)

Score against evidence, not intent. A claim with no number or artifact scores zero.

Nine Axes (score each 0-10)

Axis Scores 10 when Scores 0 when
Requirements Functional, NFR, and out-of-scope written with owners Only a feature description exists
Capacity evidence Peak QPS, storage, and bandwidth computed and current Numbers absent or older than the last traffic change
Redundancy No SPOF; failover drilled with a measured RTO Single instance or untested failover on a critical path
Data scaling Access patterns mapped, ownership single, growth path stated One shared store, no growth plan, unbounded tables
Caching Hot read paths cached with TTL and invalidation defined No cache on a proven hot path, or uninvalidatable cache
Async offload Slow and bursty work queued with drain rate and DLQ Everything synchronous on the request path
Observability Traffic, error, latency, saturation instrumented with owned alerts Logs only, or alerts with no runbook
Rollout Canary or flag with metric rollback trigger and reversible migrations Big-bang deploy, irreversible migration
Cost proportionality Spend is sized to the traffic and the risk, and someone can state it Topology bought for an imagined scale nobody measured

Report each score with the evidence used, out of 90. Weight axes by the system's actual risk: a 100 RPS internal tool is not failed for lacking multi-region.

Review Method

  1. Establish ground truth first: current traffic, data volume, incident history, and the top pain the owner reports.
  2. Score the eight axes against artifacts and metrics; mark any unverifiable claim UNVERIFIED.
  3. Trace the hottest and the most critical path end to end; the worst hop is the real bottleneck.
  4. List findings as severity - axis - evidence - consequence - smallest fix.
  5. Convert findings into a roadmap: stop-the-bleeding now, structural next, optional later.
  6. Check operability: who runs this at 3am, which team owns which piece, and whether that team can actually operate it.

Read the full file on GitHub · 69 lines

Files

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.

Changes

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.

  1. 12d ago First seen · 69 lines · 55 tokens per session scan A c7b824bff9dc

Subscribe to this mod's changes

system-design-review is a skill published in the GitHub repository HoangNguyen0403/agent-skills-standard (565 stars, last pushed 3d ago), licensed MIT. It adds 55 tokens to every session and 827 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.

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